#Gen AI in resource management

[generative-ai-in-bi]

How Does Gen AI Make Resource Allocation Cost-Efficient?

Find out how Gen AI enhances cost-efficiency in resource allocation with cutting-edge algorithms and data insights for smarter business decisions.

In the contemporary business world, strategy implementation requires proper management of resources to sustain organizational competitiveness. Resource allocation is a critical capability for today’s businesses as it enables efficient and effective resource usage as a way of optimizing profits and reducing costs. However, most traditional techniques for resource allocation are defective since the data used are either inaccurate or insufficient to exact resource optimizations. This is where Generative AI (Gen AI) comes into play. Gen AI is revolutionizing the way businesses approach the management of their resources through increased efficiency, operational costs, and responsiveness to changing market conditions, all due to its use of sophisticated algorithms and access to large quantities of data.

Generative AI offers a new dimension in the concept of cost because they make data as the center of resource management plans. Through its real-time analysis of large datasets, Gen AI can help businesses make better decisions on the deployment of their resources. In terms of inventory, workforce, or supplies, Generative AI guarantees the spending of available resources to the least possible extent. As mentioned above the advantages of implementing Gen AI in resource management is not a pipe dream; there are already companies across industries that are realizing lower operational costs and higher efficiency.

Predictive Analytics for Demand Forecasting

The most significant application of Generative AI in the allocation of resources is its predictive analytics use in demand forecasting. Gen AI uses historical data to make persistent analyzes and draw the corresponding conclusion of future demand for products and/or services. It is most applicable in the management of inventory since both overstocking and stock-outs can be very costly. Overstocking means keeping excess inventory leads to the consumption of company capital, and stock-outs lead to lost business and customers’ disappointment. This is where Generative AI can help with demand forecasting, allowing businesses to have just the right amount of stock which is optimal for fulfilling customer needs without overstocking.

For example, a retailer leveraging Gen AI for demand forecasting can plan for increased demand of certain products during festive occasions and replenish their stock in advance. This approach reduces the probability of overstocking, but also helps to avoid stock-outs and hence the use of resources and costs are optimized. Within industries like manufacturing where raw materials and production schedules need to be carefully managed, Generative AI can forecast fluctuations in demand and optimize the supply chain as well, further reducing costs and improving efficiency.

Optimizing Workforce Allocation

There are other important area like workforce management where Generative AI can drive significant cost efficiencies. Typically, workforce management often involves manual scheduling, and this causes some problems such as high levels of inefficiency in utilization of labor resources, which include time wastage and over-time costs. As for generative AI, it is capable of identifying workforce needs of a company based on project requirements, skills and workload balances. This way, it avoids issues such as over staffing, which may lead to wastage of resources, or understaffing that may slow down productivity.

For example, in a manufacturing plant, Gen AI is capable of estimating peak and off production seasons and then schedule the employees. For instance, the AI could recommend hiring additional workers during peak production periods as well as downsizing during slower periods. Such a level of precision in workforce allocation not only reduces idle time and overtime expenses but also enhances overall productivity. Several companies that have integrated AI in workforce management solutions have realized better control of workforce costs and increased employees’ satisfaction since the workforce is well-matched with the business needs.

Enhancing Supply Chain Efficiency

Supply chain management usually involves a cocktail of issues including supplier selection, logistics, and inventory management which all have the tendency of contributing to the over cost of the overall chain. The innovation of generative AI presents a powerful solution to these challenges since it improves the transparency and flow of supply chain. Gen AI is also very effective in analyzing data from all supply chain links from the procurement of raw materials to final product delivery; Gen AI can identify cost-effective suppliers, optimize logistics routes, and streamline inventory management.

For instance, Generative AI can analyze historical data to identify the best suppliers regarding delivery time, quality, and price in the supply chain. It also simplifies the process of finding new sources and can help to negotiate for better prices and improved supply chain reliability. As for the concept of logistic, Gen AI can easily find the best routes to transport goods, reducing fuel consumption and delivery times, which directly translates into cost savings. Further, by providing real-time insights into inventory levels, Generative AI is also important in eliminating excess stock and stock out situations hence increasing the efficiency of the supply chain and decrease operational costs.

Dynamic Pricing Models with Gen AI

Dynamic pricing is a method through which prices for products and services are varied according to the current market conditions. Generative AI helps to integrate flexible pricing strategies into enterprises with high levels of accuracy based on market changes. Having information about the customer behavior, competitor actions, and broader economic trends, Gen AI can suggest the optimal price adjustments that balance competitiveness with profitability.

For instance, an e-commerce platform with Gen AI to apply dynamic pricing will reduce product prices during low demand in the market in order to increase its sales revenue, and increase prices during high demand to increase its profits. This flexibility in pricing helps businesses want to remain relevant and at the same time make profits without having to compromise on its profit margins. Companies that have adopted the use of AI in pricing strategies have disclosed that they have realized an increase in revenue and profit margins, as they are able to respond more quickly and effectively to market changes.

Energy Consumption and Sustainability

The cost of energy consumption for a business is one of its significant expenses depending on the industry where it operates, specifically those relying heavily on energy, such as manufacturing industries and other sectors utilizing large amounts of energy. As for the challenges and the solutions, there are still some challenges to be addressed that lead to Generative AI’s major advantage of improving efficiency in energy consumption and leading to cost reduction for renewable energy, which in turn makes a positive impact toward achieving sustainability. Because the patterns of energy use, equipment performance, and production schedule can be monitored and analyzed, Gen AI can suggest changes to optimize energy use and increase efficiency.

For example, in the manufacturing environment, Gen AI can use data from sensors installed in manufacturing equipment to identify low energy consumption time and recommend changes to the schedules or equipment settings. This not only lowers energy costs but also supports the company’s sustainability initiatives by reducing its carbon footprint. Industries like automotive manufacturing where energy cost forms a good fraction of the total cost have already started realizing benefits of AI-driven energy management with companies recording improvements in energy consumption of more than 20%.

Risk Management and Cost Control

It is crucial to function as a risk management practice since uncontrolled risks may significantly impact the company’s profitability. Generative AI plays a crucial role in risk management, as it helps to determine risks before they occur and provides recommendations on how to avoided them. Using historical data, trends, and various indicators, Gen AI can predict potential disruptions and recommend ways of preventing or mitigating them.

For instance, in the financial sector of a business, Gen AI can look at the market tendencies, identify emerging economic risks that might affect either a company’s investment or operations. Through early identification of these risks, the AI enables the management to make necessary changes, including adjusting investment portfolios or resource allocations, to minimize loss. This proactive approach not only lowers the probability of losses, but also helps in better dealing with the budget management, as the resources can be distributed with more precision if the risks are taken into consideration.

Continuous Learning and Improvement

One of the major benefits of Generative AI is that it expands and develops a model while working on it. Unlike traditional systems, Gen AI receives new data more often and updates its algorithms for efficient resource allocation. This continuous learning process makes certain that the AI in cost management is always up to date achieving further improved levels of effectiveness and efficiency.

For example, in a retail context, Gen AI might initially analyze sales data to optimize inventory levels. As the customer data and seasonal trends are accumulated or the conditions of competition changes, the AI system would move to more effective recommendations of solution making the whole process cost saving and more efficient. Such continuous improvement process plays an important role in contemporary business environment in order to cope up with emerging business environments.

Conclusion

This is what generative AI is doing for businesses as it brings efficiency, flexibility, and profitability to resource management. Besides, more operational expertise, workforce and supply chain management, flexible pricing, and risk management allow Gen AI to greatly contribute to cost cutting and increased effectiveness. With the progressing advancement of Generative AI systems, it will be to businesses’ advantage to allocate the power of this technology to resource management. It is for this reason that cost management of the future is already here, and it is driven by Generative AI.

Original Source : https://bit.ly/4grgQU7

[doktorpeace]

The Great All Generation Nuzlocks Roundup

This is gonna be long and have multiple parts thanks to the image limit on posts. Each game will be headlined by their title in Bold Print so if you're only interested in certain games it'll be easy to filter through. These notes will also only be on the Successful Run of each game. I'll note how many times I wiped in each game, but largely won't mention those runs for sake of relative brevity.

All runs were performed with the following rules - Only One Encounter Per Route/Zone/Area/Cave [Unique Names Denote Separate Areas] No Duplicate Encounters No Using Items In Battle No In-Game Trades No Overleveling the next Gym Leader or Major Boss Purchased/Gift Pokemon Are Allowed (Though there is only one case where I use one) but count as your encounter for that Area. No Use Of 'Affection' Based Mechanics.

RED - Kanto is a genuine joy to Nuzlocke for a few reasons. It's quick to get going, most early game Pokemon are quite strong (Ratticate, Primeape, Nidoking/queen, and Fearow are all genuinely incredible encounters), and it has probably the most balanced set of starters overall with regards to choice. All three have viable reasonings to be picked in the context of a nuzlocke. I, personally, went with Bulbasaur because my primary goal was to Win The Game and not to flex.

Kanto's also great for developing basic skills for nuzlocking. Team building, knowing when to switch, resource/Power Point management, moveset scouting, etc. all go much farther than normal in Kanto thanks to the poor AI and generally weak enemy trainers.

My favorite thing about it, though, and what made it very fun and a great start is that unlike every other region you can 100% assure yourself VERY powerful encounters in the mid and late game, and I don't mean gift Pokemon. There's just so many routes where all the encounters are filler you're 100% going to have out of the way early (Ratata, pidgey, etc.) that it's a surefire thing that you WILL get a Doduo right outside Celadon, for instance. Extending this to the whole region, you can guarantee you get other extremely potent Pokemon like Slowbro, which I did.

My team in this one was a strong Water/Fire/Grass core and otherwise strong goodstufts that compliment one another well. The surprise of this run was definitely Arcanine. I remember as a kid really being underwhelmed with trying to raise a Growlithe and never really getting the hype behind Arcanine outside of a VGC setting. However, I realized as an adult that keeping it a Growlithe until level 50 for flamethrower is Stupid. I immediately evolved that sucker and taught it Dig, which has 100 base power in gen 1. Arcanine was able to coast off of Dig and Body Slam until we beat Blaine and got the Fire Blast TM. It can also learn Reflect in this gen! All in all a stellar team member whose absolutely massive stats right after obtaining at level 19 really let it shine!

I always forget just how absurd the level swing from even just Lorelei to Blue is though. Just an absolute cliff of increase. Thankfully, however, leveling up in Kanto is a non-issue, so I was able to keep pace even while abiding Hardcore Nuzlocke rules. Total Wipes - 0

CRYSTAL - My overall opinion on Johto really hasn't changed at all, lol. It's still suffers a lot from what I'll call 'Fake Nonlinearity'. Like, sure, you CAN go to a lot of places after beating Morty but like...why would you do anything but go Chuck->Jasmine->Pryce and their associated content? It's not like you can meaningfully get strong early since the entire region has a dearth of strong trainers and wild pokemon alike. It's simply not productive to do things outside of the obviously intended order, except perhaps in the context of a Nuzlocke and trying to get some encounters early.

What does give Nuzlocking this region a unique flavor is that the best pokemon in the game, Alakazam, is a 100% ensured encounter assuming you're willing to pass over the free Eevee from Bill, which you should be. For a mere 200 coins at the game corner, you can get an Abra which can immediately be taught all 3 elemental punches on the cheap and raised up. Johto Nuzlockes thus take the form more of building an ensemble cast to support your clear Main Character, rather than building a cohesive team. As a result, Steelix and Machamp greatly stood out for being so dramatically different from Alakazam that they could patch up his few deficiencies.

We faced a setback VERY late and lost our Tauros on Victory Road, leading to the emergency training of Golly the Politoed. He ended up doing almost nothing, but that's true for the entire team besides Pugilist, who swept the entire Elite 4 and Lance unassisted.

It was definitely a fun time and had a very unique flavor compared to other regions. What Johto offers it does offer uniquely, at least.

Total Wipes - 2 (Rival Fight in Azalea Town Gym Leader Morty)

EMERALD - I'm gonna be totally honest. I love Hoenn and I love Gen 3 but I had somehow never actually pushed all the way through Emerald before. I've beaten Sapphire and ORAS each several times, so there was some nice new stuff to me waiting. Emerald is the first game you can play that still feels 'Modern' even without the Phys/Special split. The gameplay design, routes, and everything else just feel much more well realized and iterated upon, which makes sense. Gen 2 was made to capitalize on the Pokemon Craze where Gen 3 was made with the idea of 'Oh, we have a long running thing on our hands.' They worked to impress!

That said, I don't have all that much to say! Emerald is a very Standard Pokemon game and I had a lot of fun with it. I did end up repeating a single pokemon on my endgame team, Gyarados, but most of the run was played without it. I simply blundered a good number of strong encounters away in the midgame and had to fall back on a Pokemon I knew would be strong and could help get me through the Elite 4 and Juan!

This team has a very funny Water/Fire/Grass/Water/Grass core and it's also the first game where I actually EV trained my team on purpose. Thanks to Gen 3's thoughtful encounter design, training up Sp. Attack, HP, Speed, and Defense are all trivial, which greatly helped out. Sunny Day on Ludicolo was specifically to counter Juan, and we NEEDED it too because we lost Gyarados to Drake and Juan got TWO FREEZES in that final battle, so I needed Ludicolo to put in extra work. All in all, this was definitely one of my weaker Final teams, but I partly blame that on my relative unfamiliarity with Emerald's mid and late game. I also simply was not using all the resources at my disposal, which would dramatically change starting with the next game. The big surprise was honestly Electrode, who was a pretty stellar and reliable teammate all through the late and endgame due to fast, strong thunderbolts and screens support.

This game had a nickname theme - Fruits.

Total Wipes - 1 (Gym Leader Brawly)

PLATINUM - If you've followed me long enough you know I've historically been very hard on Gen 4. I do not like Diamond/Pearl and have started and dropped Platinum many times. However, this run I had a genuine joy playing through. Really and truly, playing in this format with the momentum of three runs behind me energized me to see Sinnoh in a new light and I can truly appreciate the dramatic improvements Platinum makes to the region. Most importantly, I've made a new, lifelong friend.

Encountered as a Nosepass at level 14 in Mt.Coronet, Cao Cao was a true champion and help throughout the midgame and into the early late game. Stonewalling tons of trainers, enabling easy captures on lots of encounters, offering free and important switches at critical moments, and just generally being a reliable member of our core duo for most of the game with Rotom Fan...but we lost him at Iron Island in a completely optional double battle... (artist's rendition in the workbench room at my office)

To make matters worse, the teammate we went to Iron Island for, our Scyther so we could evolve her into Scizor, would also be lost shortly before the Elite 4, rendering his loss all the more painful! I knew, for him, we had to carry on and we had to win.

And win we did. My total unfamiliarity with Platinum past the first couple gyms had me doing much more planning and research out of game on upcoming trainers to help ensure a strong run. As a result we lost far less team members than in the past three runs. In particular I was really sweating the encounters with Barry, who is dramatically stronger than previous rivals. But really, we didn't have any noteworthy losses to him.

Platinum is certainly a challenging game in its back quarter but it also really squanders its otherwise quite excellent pacing in the first two thirds or so of the game. After the sixth gym the game gets really long in the tooth and I was just ready for it to be over by the end. Nonetheless, I did have quite a lot of fun and when I play Platinum again in the future I'll definitely do it as a more casual nuzlocke, for fun.

For the vast majority of this run I had a Rotom Fan, Probopass, and Scizor but they were all lost somewhat to VERY late and were replaced with the bottom row. While Whiscash and Porygon 2 stepped right up and were excellent performers, Bronzong was absolutely abysmal and did nothing but provide a single free switch against Cynthia. This run also came closest to dying, with only Crobat surviving the champion battle. (in my heart, however, any team that completes the game all get to go on and I have in fact transferred them into pokemon home, lol) Wuxuan the Crobat was basically my true starter. With me from before the first gym and all the way through to the end. A stellar pokemon. While this run endeared me to many Pokemon I hadn't used in game - or at all - before in Rapidash, Crobat, and Rotom Fan, above them all stands my new true friend, Probopass.

This run was downright cursed when it came to natures, too. Basically every single encounter had a nature that was negative on their most important stat. It was really frustrating, tbh!

This game has the second and final case of a team having a duplicate species of a previous team - Machamp This game has a nickname theme - Romance of the Three Kingdoms

Total Wipes - 0

Post will continue in a Part 2 because of the post image limit.

[fourhornedsatyr]

As an avid fan of Mike Pondsmith's Cyberpunk setting I cannot help but just look at the year 2024 in the US and be like: Yea Mike, you were a little off and a bit ahead, or a lot, but like holy fuck the internet and cyber tech has been so misused and is now the tool of corporations to fuck us over.

First off, phone phishing??? I have spam filters and still get 2-5 phishing phone calls a day that, if I do pick up, try to trick me into giving away my voice and data. This has become so common that literally no one I know answers a call unless they know the number or are actively awaiting a call from an unknown number (for job interviews, appointments, etc).

We, on the regular, deal with AI that is meant to steal our voices, names, and other cruical data. This has brought us to manage unknown numbers the same way we manage superstitious entities such as fae in fairy tales. How fucked up is that?

Streaming, once an alternative to and then a replacement of video stores, has come to replace TV and is severely less consumer friendly as access to media has become severely fragmented by the corporate nature of these services. I won't even get into the decreasing quality of popular media, just simply look at Disney to see the shift.

Social media? Something that was meant to connect family, friends, and community? Yea, that's now a sespool of ads, has algorithms that will try to feed you misinformation, and has been made into an addictive drug meant to keep people seperated and inactive in the freetime that we have.

There's come a large group of people in my generation (gen Z) and those who came before us (Millenials), who simply do not pay for our media. Piracy of old and new movies, shows, videogames, music, and even books has simply become the norm because we cannot afford to pay for it, and what we can access on the corpo sites has been severely reduced in quality by easily evaded ads.

And what do I have to say to that? We live in a capitalist society and we gotta play the game to live until we break it. They can't create a product that we're willing to use? Boohoo, someone outcompeted them by providing us with a product that removes ads that only serve to degrade, seperate, or comodify us. Corporations act like they deserve our subservience, money, and labor -- they don't.

Moving on from just entertainment and social media, search engines, our phones, and nearly everything we have to access the internet is used to track us and sell our data so that we may be comodified more efficiently by the corpos. We may say "I'm gonna google that", but many of us have stopped using google and other engines because of how bad they are at actually giving us good results. Task specific search engines and ones that don't track or sell our data (like duckduckgo) have become common place.

Also, just, most people do not own their own media? Some people don't own a single movie, show, song, book, videogame, or any other digital media and instead opt to stream them (ie spotify) or purchase access to them (ie steam). I know very few people in my generation who own a cd player or any type of physical music, and it just throws me.

The internet and digital tech could have been so much better and can do so much good, but no, it's used for capitalism instead.

Wage theft, job theft, piracy, and phishing.

Down with the capitalist system, let's bring on a future wherein our art, knowledge, social forums, and automatons are not weaponized against us so that we may share the resources we need to survive, thrive, and live fulfilling lives.

[plotholes-and-spellingerrors]

But I think the point is that the "AI" (marketing term) that was used for Spiderverse is NOT THE SAME TECHNOLOGY as the "AI" (marketing term) that outputs simulacrums of text or images as a response to user input, right?

Like, [a stand mixer] and [every item in your kitchen drawers duct taped to the business end of a a V8 625 HP outboard motor] are both, technically, kitchen appliances. But one is purpose-built for a specific task, and one is both ridiculously over-powered while also being almost unusably broadly specified. The stand mixer is a $200 one-time purchase that lives in your house on your kitchen counter, whereas the 625 HP omnitensil is a $20 monthly subscription that runs on gasoline and that can only be used at the omnitensil depot. You could, probably, baby-sit and micro-manage the All The Food Everywhere All At Once Device to the point of getting something that resembles a beaten egg (and most of it sill in the bowl, even! ...Though you did need to hand-craft a bowl that could contain the egg during the procedure) but at that point, why not just buy the stand mixer?

The point is that the Spiderverse folks didn't HAVE to micromanage a "generative AI" model to get it to output every frame with a line in the right place, because they were not using a "generative AI" tool.

(And this is my personal opinion here, but I'm not sure that gen ai will ever be able to be as good as something like a rendering program or a photoshop brush because those are tools built and optimized for a specific task, whereas "gen ai" is intended to be a "general intelligence" - capable of doing whatever. But there's so much that can be asked of such a tool that I think there's not enough data in the world to effectively train it and it would be too computationally expensive to do so... and if you managed to make it anyway, it would be so resource-heavy to run that there would be zero reason to use it in favor of a smaller, simpler, purpose-built tool.)

Anyway, thanks for reading my late-night rant lol

[govindhtech]

​HTTP 429 Errors: Keep Your Users Online And Happy

429 Errors

Avoid leaving your visitors waiting when resources run out: How to deal with 429 errors

429 error meaning

When a client sends too many requests to a server in a specified period of time, an HTTP error known as “Too Many Requests” (Error 429) occurs. This error can occur for many reasons:

Rate-limiting

The server limits client requests per time period.

Security

A DDoS attack or brute-force login attempt was detected by the server. In this instance, the server may block the suspect requestor’s IP.

Limits bandwidth

Server bandwidth is maxed out.

Per-user restrictions

The server has hit its maximum on user requests per time period.

The mistake may go away, but you should fix it to avoid losing traffic and rankings. Flushing your DNS cache forces your computer to acquire the latest DNS information, fixing the issue.

Large language models (LLMs) offer developers a great deal of capability and scalability, a seamless user experience depends on resource management. Because LLMs require a lot of processing power, it’s critical to foresee and manage possible resource depletion. Otherwise, 429 “resource exhaustion” errors could occur, which could interfere with users’ ability to interact with your AI application.

Google examines the reasons behind the 429 errors that LLMs make nowadays and provides three useful techniques for dealing with them successfully. Even during periods of high demand, you can contribute to ensuring a seamless and continuous experience by comprehending the underlying causes and implementing the appropriate solutions.

Backoff!

Retry logic and exponential backoff have been used for many years. LLMs can also benefit from these fundamental strategies for managing resource depletion or API unavailability. Backoff and retry logic in the code might be useful when a model’s API is overloaded with calls from generative AI applications or when a system is overloaded with inquiries. Until the overloaded system recovers, the waiting time grows dramatically with each retry.

Backoff logic can be implemented in your application code using decorators in Python. For instance, Tenacity is a helpful Python general-purpose retrying module that makes it easier to incorporate retry behavior into your code. Asynchronous programs and multimodal models with broad context windows, like Gemini, are more prone to 429 errors.

To show how backoff and retry are essential to the success of your gen AI application, Google tested sending a lot of input to Gemini 1.5 Pro. Google is straining the Gemini system by using photos and videoskept in Google Cloud Storage.

The results, where four of five attempts failed, are shown below without backoff and retry enabled.the results without backoff and retry configured

The outcomes with backoff and retry set up are shown below. By using backoff and retry, all five tries were successful. There is a trade-off even when the model responds to a successful API call. A response’s latency increases with the backoff and retry. Performance might be enhanced by modifying the model, adding more code, or moving to a different cloud zone. Backoff and retry, however, is generally better in times of heavy traffic and congestion.The results with backoff and retry configured

Additionally, you could frequently run into problems with the underlying APIs when working with LLMs, including rate-limiting or outages. It becomes increasingly crucial to protect against these when you put your LLM applications into production. For this reason, LangChain presented the idea of a fallback, which is a backup plan that might be employed in an emergency. One fallback option is to switch to a different model or even to a different LLM provider. To make your LLM applications more resilient, you can incorporate fallbacks into your code in addition to backoff and retry techniques.

With Apigee, circuit breaking is an additional strong choice for LLM resilience. You can control traffic distribution and graceful failure management by putting Apigee in between a RAG application and LLM endpoints. Naturally, every model will offer a unique solution, thus it is important to properly test the circuit breaking design and fallbacks to make sure they satisfy your consumers’ expectations.

Dynamic shared quota

For some models, Google Cloud uses dynamic shared quota to control resource allocation in an effort to offer a more adaptable and effective user experience. This is how it operates:

Dynamic shared quota versus Traditional quota

Traditional quota: In a Traditional quota system, you are given a set amount of API requests per day, per minute, or region, for example. You often have to file a request for a quota increase and wait for approval if you need more capacity. This can be inconvenient and slow. Of course, capacity is still on-demand and not dedicated, thus quota allocation alone does not ensure capacity. Dynamic shared quota: Google Cloud offers a pool of available capacity for a service through dynamic shared quota. All of the users submitting requests share this capacity in real-time. You draw from this shared pool according to your needs at any given time, rather than having a set individual limit.

Dynamic shared quota advantages

Removes quota increase requests: For services that employ dynamic shared quota, quota increase requests are no longer required. The system adapts to your usage habits on its own.

Increased efficiency: Because the system can distribute capacity where it is most needed at any given time, resources are used more effectively.

Decreased latency: Google Cloud can reduce latency and respond to your requests more quickly by dynamically allocating resources.

Management made easier: Since you don’t have to worry about reaching set limits, capacity planning is made easier.

Using a dynamic shared quota

429  resource exhaustion errors to Gemini with big multimodal input, like large video files, are more likely to result in resource exhaustion failures. The model performance of Gemini-1.5-pro-001 with a traditional quota and Gemini-1.5-pro-002 with a dynamic shared quota is contrasted below. It can be observed that the second-generation Gemini Pro model performs better than the first-generation model due to dynamic shared quota, even without retrying (which is not advised).model performance of Gemini-1.5-pro-001 with traditional quota versus Gemini-1.5-pro-002 with dynamic shared quotamodel performance of Gemini-1.5-pro-001 with traditional quota versus Gemini-1.5-pro-002 with dynamic shared quota

Dynamic shared quota should be used with backoff and retry systems, particularly as request volume and token size grow. In all of its initial attempts, it ran into 429 errors when testing the -002 model with greater video input. The test results below, however, show that all five subsequent attempts were successful when backoff and retry logic were used. This demonstrates how important this tactic is to the consistent performance of the more recent -002 Gemini model.

A move toward a more adaptable and effective method of resource management in Google Cloud is represented by dynamic shared quota. It seeks to maximize resource consumption while offering users a tightly integrated experience through dynamic capacity allocation. There is no user-configurable dynamic shared quota. Only certain models, such as Gemini-1.5-pro-002 and Gemini-1.5-flash-002, have Google enabled it.

As an alternative, you may occasionally want to set a hard-stop barrier to cease making too many API requests to Gemini. In Vertex AI, intentionally creating a customer-defined quota depends on a number of factors, including abuse, financial constraints and restrictions, or security considerations. The customer quota override capability is useful in this situation. This could be a helpful tool for safeguarding your AI systems and apps. Terraform’s google_service_usage_consumer_quota_override schema can be used to control consumer quota.

Provisioned Throughput

You may reserve specific capacity for generative AI models on the Vertex AI platform with Google Cloud’s Provisioned Throughput feature. This implies that even during periods of high demand, you can rely on consistent and dependable performance for your AI workloads.

Below is a summary of its features and benefits:

Benefits

Predictable performance: Your AI apps will function more smoothly if you eliminate performance fluctuation and receive predictable reaction times.

Reserved capacity: Queuing and resource contention are no longer concerns. For your AI models, you have a specific capacity. The pay-as-you-go charge is automatically applied to extra traffic when Provisioned Throughput capacity is exceeded.

Cost-effective: If you have regular, high-volume AI workloads, it can be less expensive than pay-as-you-go pricing. Use steps one through ten in the order process to determine whether Provisioned Throughput can save you money.

Scalable: As your demands change, you may simply increase or decrease the capacity you have reserved.

Image credit to Google Cloud

This would undoubtedly be helpful if your application has a big user base and you need to give quick response times. This is specifically made for applications like chatbots and interactive content creation that need instantaneous AI processing. Computationally demanding AI operations, including processing large datasets or producing intricate outputs, can also benefit from provisioned throughput.

Stay away with 429 errors

Reliable performance is essential when generative AI is used in production. Think about putting these three tactics into practice to accomplish this. It is great practice to integrate backoff and retry capabilities into all of your gen AI applications since they are made to cooperate.

Read more on Govindhtech.com

[16by64mediaproduction]

Corporate Event Trends in 2025 - What’s shaping up

As we stand ready to welcome 2025, the corporate events industry is rapidly changing the format of their events towards wellness and sustainability. Corporate professionals are getting ready to take part in events that are modern, impactful, and immersive. Here, in this blog, we have listed some of the top trends in the field of corporate events worldwide that reflect these changes.

Why hybrid events is the new standard

The hybrid event format, in corporate event planning, combining in-person and virtual elements is here to stay. Hybrid events improve flexibility allowing participants from across the globe join and interact via virtual tools such as Q&A, live polls, and AI-driven networking. Here in India, hybrid business events offer convenience and inclusivity, well-suited for an increasingly digital and mobile workforce.

Sustainability – what it means in corporate events

Environmental consciousness finds the top spot in any corporate event today. Corporate event agencies choose eco-friendly venues to minimize plastic usage. It is also observed that sustainable practices are cruciform the yardstick for brands that want to be seen or heard in the marketplace. Picking out green-certified venues is the number one priority for corporate event management companies to reduce carbon footprint. Using digital resources and locally sourced materials are other requirements. These improve brand image while fostering a positive experience.

Immersive team-building experiences

Immersive, scenario-based experiences that foster collaboration and creative problem-solving are the most sought-after corporate team-building activities. In high-energy environments, office team-building activities provide memorable times offering employees a chance to strengthen bonds with their team members.

Wellness-focused corporate retreats and benefits

Wellness is becoming central theme of many corporate retreats, reflecting the growing awareness of interlinked mental and physical health. Wellness retreats feature close-to-nature activities, digital detox periods and mindfulness sessions, help employees relax and recharge and recoup. This works well for professionals whose work environments are stressful and helps to better individual performance.

Impact of AI and personalization

AI is transforming business events by enabling deeper personalization among participants. This fulfils new-gen expectations with deeply personalized digital experiences and use of  AI-powered tools help to reach out to every attendee and improve overall learning.

Experiential setups/pop-up events – what they mean

Pop-up events and experiential setups are popular, transforming ordinary spaces into themed, interactive environments. The novelty and aesthetics appeal particularly to young professionals and make for more intimate networking opportunities.

Diversity and inclusion in business events – long-term advantages

Corporate retreats in 2025 will be prioritizing diversity and inclusion if trends are something to go by. This means making every participant feel welcome:  by including diverse panels of speakers, making available more accessibility options, and serving inclusive menus. Such an approach would make way for spreading a culture of respect and reflect the company’s standing in the marketplace.

Closing notes

Business events are not going to be just social learning gatherings in the coming year; they would be complete experiential venues that reflect a company’s vales and commitment to wellness, innovation, and inclusivity. Hybrid formats, personalized AI-driven experiences and sustainable practices will help companies create events that resonate with modern life and trends.

Corporate events – what they will likely be made of in 2025 and benefits of the new approach

The Global Event Industry Benchmarks and Trends: 58% of organizations will continue to use hybrid events, in spite of in-person gatherings happening. Close to 67% of event planners mention that hybrid events have increased event attendance (Source: PCMA, 2024).

The 2024 Sustainable Event Industry Report: 79% of event planners have adopted sustainability practices and 72% of attendees feel more positively about brands that showcase eco-friendly events (Eventbrite, 2024).

The 2024 Corporate Events Survey: 63% of companies include VR/AR into team-building activities, and 85% of participants have reported higher engagement during such events (MPI Report, 2024).

A 2024 survey by the Global Wellness Institute: 78% of companies believe wellness-based retreats boost employee morale and serve to reduce burnout. Such events have seen 52% popularity growth than previous years (Global Wellness Institute, 2024).

Recent study: 62% of event planners currently use AI to deepen event personalization to create customized schedules and curated content for attendees (Cvent Report, 2024).

The Event Marketing Institute report: 55% of brands plan to increase their experiential marketing budget, and 41% have observed a more positive impact through pop-up events (Event Marketing Institute, 2024).

Recent survey: 73% of companies now actively incorporate diversity and inclusivity elements in their events(Event Managers Association, "Diversity and Inclusion in Events," 2024).

FAQs

Are hybrid events going to be popular in 2025?

Hybrid events combine in-person and virtual experiences. They have been observed to boost attendance, flexibility, and accessibility, making them a key 2025 trend.

2. How do sustainability practices impact business events?

Sustainable events are designed to reduce waste by using eco-friendly materials. This means a positive impact on the brand’s image and fulfilment of today’s young professionals' environmental values

3. Why is wellness so popular in corporate retreats?

Wellness-based corporate retreats improve employee morale, take care of burnout, and boost productivity, especially in today’s high-stress corporate environments.

[fromdevcom]

When choosing between a knowledge graph and a vector database for smart data handling, it's essential to grasp the advantages and applications of each. Each technology provides effective methods for handling and searching data, yet they are designed for various purposes and situations. Knowledge Graphs: Structured Relationships Knowledge graphs are highly effective at capturing and querying relationships between entities. They organize data into nodes (representing entities) and edges (representing relationships), creating a graph-based structure. This arrangement supports intricate queries that can explore relationships, making knowledge graphs particularly well-suited for situations where the connections between data points are as crucial as the data itself. For example, in a knowledge graph, you might have nodes representing people, organizations, and events. The edges between these nodes can represent relationships like "works for," "attended," or "founded." This allows for queries like "Which people attended events hosted by a specific organization?" to be executed efficiently. Knowledge graphs are particularly powerful in domains like recommendation systems, fraud detection, and knowledge management. They are also widely used in semantic search engines, where understanding the meaning behind search queries requires a deep understanding of the relationships between concepts. Vector Databases: Managing Unstructured Data Vector databases are specifically built to manage unstructured data, including text, images, and audio. They represent data as high-dimensional vectors, which mathematically capture the essence or meaning of the data. This enables similarity searches, allowing you to find data points that are "close" to each other in vector space, even if they are not exactly the same. In a vector database, text can be transformed into a vector that captures its underlying meaning. These vectors can then be compared to identify similar texts, even when the words used differ. This makes vector databases particularly useful for tasks such as semantic search, recommendation systems, and natural language processing. Vector databases are increasingly being used in applications that involve AI and machine learning. They are well-suited for managing large-scale, unstructured data where traditional databases might struggle. Choosing the Right Technology When deciding on a knowledge graph or a vector database, the key consideration is the nature of your data and the type of queries you need to perform. Data Structure If your data is highly structured, with clear entities and relationships, a knowledge graph is likely the better choice. Knowledge graphs are optimized for handling structured data and can efficiently execute complex queries that involve multiple relationships. Query Requirements If your queries involve traversing relationships or understanding the connections between data points, a knowledge graph is more suitable. For example, if you need to find all individuals connected to a specific entity through multiple relationships, a knowledge graph can handle this with ease. Unstructured Data If your data is largely unstructured, such as text, images, or audio, and you need to perform similarity searches, a vector database is the better option. Vector databases are designed to handle the challenges of unstructured data and can perform searches based on the meaning or content of the data rather than exact matches. Scalability Non functional requirement scalability is important for your application. Knowledge graphs can scale well for structured data, but they may require significant computational resources as the complexity of the graph increases. Vector databases, on the other hand, are designed to handle large-scale unstructured data and can scale more easily for applications involving AI and machine learning. Integration with AI If your application involves AI or machine

learning, especially tasks like recommendation systems or natural language processing, a vector database is likely the better fit. Vector databases can easily integrate with AI models and handle the high-dimensional data that these models generate. Use Cases for Knowledge Graphs Knowledge graphs are best for applications where it's important for the stakeholders to understand and navigate relationships between data points. Here are some common use cases below: Recommendation Systems: Knowledge graphs can enhance personalized recommendations by analyzing the relationships between users, products, and their preferences. Fraud Detection: In financial services, knowledge graphs can help identify suspicious patterns by analyzing the relationships between transactions, accounts, and individuals. Knowledge Management: Organizations use knowledge graphs to organize and retrieve information efficiently, making it easier for employees to find relevant data. Supply Chain Management: Knowledge graphs can help track and optimize supply chain processes by mapping relationships between suppliers, manufacturers, and distribution networks. Use Cases for Vector Databases Vector databases are best suited for applications involving unstructured data and similarity searches. Common use cases include: Semantic Search: Vector databases can enhance search engines by allowing them to understand the meaning behind queries and find relevant results, even if they don't contain the exact keywords. Recommendation Engines: By comparing user preferences and behavior, vector databases can recommend similar items, even if the user hasn't explicitly searched for them. Natural Language Processing: Vector databases can store and query the vectors generated by language models, enabling applications like chatbots, sentiment analysis, and machine translation. Image and Video Retrieval: Vector databases can search and retrieve similar images or videos based on content, enabling applications like visual search and media recommendation systems. Conclusion Choosing between a knowledge graph and a vector database hinges on what your application requires. Knowledge graphs are more appropriate for organized data and intricate queries about relationships, whereas vector databases are more effective at managing unorganized data and searching for similarities. Grasping the characteristics of your data and the demands of your queries will assist you in selecting the appropriate technology for smart data handling. By selecting the appropriate technology, you can ensure that your data management strategy is aligned with your business goals, enabling more effective decision-making and better insights from your data.

[danielwalkerusa]

Generative AI revolutionizes loan servicing operations by enabling smarter decision-making and efficient workflows. From automating customer interactions to streamlining document processing, it enhances accuracy and reduces operational costs. This transformative technology empowers organizations to deliver better customer experiences while optimizing resources, marking a significant step forward in the financial services industry.

[poweredbytiktik]

Staying Ahead of the Curve: Aether X by TikTik Global Redefines Software Excellence

In the fast-paced world of tech, staying current and efficient is essential. Aether X by TikTik Global has become a game-changer, setting a new benchmark for modern software. Through intuitive design, cross-device functionality, and advanced AI support, Aether X delivers a streamlined experience that empowers users. It addresses user needs in real-time, with productivity and security as its cornerstones, meeting the demands of a world that craves adaptability and ease.

Aether X: Usability Meets Cutting-Edge Innovation

Aether X by TikTik Global pushes beyond traditional software limitations with a robust, user-focused approach. Designed for those who need powerful yet accessible features, Aether X brings sophisticated capabilities to the forefront. Here are some of its most compelling qualities:

Dynamic User Interface

Aether X's user interface adapts seamlessly to various device formats and user preferences. The layout shifts smoothly from smartphone to desktop, making it easy to operate on any platform. This adaptability allows users to enjoy the same experience, whether on a smartwatch or laptop.

AI Integration for Customized Support

With AI-powered automation, Aether X assists users at every step. The software learns from user behavior, offering insights and recommendations to simplify tasks. It proactively automates daily routines, saving time and reducing the need for hands-on management.

Real-Time Cloud Synchronization

Aether X allows instant access to data across devices, supporting a fluid and uninterrupted workflow. By syncing files and updates in real time, users can switch from one device to another seamlessly, avoiding the delays of manual file transfers.

Robust Security Architecture

Security is fundamental to Aether X’s design. Equipped with biometric authentication and encryption, it secures data at every step. Real-time threat detection protects against breaches, making Aether X ideal for both personal and business use.

Enhanced Productivity Across Devices

Aether X supports productivity by combining ease of use with high-functionality tools. Its efficiency-oriented features meet the diverse needs of professionals, students, and tech enthusiasts.

Unified Workspaces: Aether X unites essential tools in one space, reducing distractions and enhancing focus. Users can quickly access what they need without navigating through clutter.

Automated Task Management: Its intelligent automation streamlines repetitive actions. With AI-driven automation, users can organize files, schedule reminders, and set up custom workflows for daily efficiency.

Cross-Device Collaboration: Real-time sync enables multiple users to work on the same file across devices. This flexibility supports collaboration, eliminating version conflicts and enhancing teamwork.

Future-Ready for Evolving Technology

Built for longevity, Aether X by TikTik Global anticipates and adapts to future technological demands, evolving alongside user needs.

Compatibility with Emerging Technologies

Aether X’s structure makes it adaptable to upcoming innovations. As new tech surfaces, Aether X’s design ensures smooth integration, keeping users at the cutting edge without major overhauls.

Scalable and Sustainable

Aether X’s resource-efficient approach supports sustainability. It optimizes device resources, reducing energy use and enhancing device longevity. Scalable for growth, it’s also a go-to for organizations expanding their digital infrastructure.

Continuous User-Centric Updates

TikTik Global continually enhances Aether X, integrating user feedback to ensure relevance and ease of use. This commitment to refinement means that Aether X will stay intuitive and functional as the digital landscape changes.

Conclusion: A New Standard in Software with Aether X by TikTik Global

Aether X by TikTik Global has redefined the possibilities of software by prioritizing user needs, offering a next-gen experience that’s both advanced and accessible. Through cross-device compatibility, advanced AI, and proactive security, it meets the demands of today’s digital age. This innovation positions Aether X as the future of software, where usability and sophistication intersect for a truly remarkable experience.

[performix]

Generative AI in the USA: Transforming Business in 2024

Generative AI (Gen AI) is reshaping industries across the USA, powering significant advancements in business operations, customer engagement, and revenue growth. Leading companies like IBM, Amazon, and Accenture are pioneering its use, providing powerful examples of how Gen AI can enhance efficiency and competitive advantage. Below, we explore the latest Gen AI advancements and offer strategies for businesses to leverage this transformative technology effectively. 

Latest Gen AI Developments from Industry Leaders 

Accenture’s AI Research 

Accenture’s research reveals that 74% of businesses investing in Gen AI have achieved positive outcomes, showing gains in both revenue growth and productivity. These benefits are especially prominent in companies that modernize processes with AI, although many still face challenges with data quality and skill gaps, which are key to unlocking Gen AI’s full potential. 

Amazon’s Gen AI Applications 

Amazon is integrating Gen AI into logistics and retail operations, using predictive analytics to enhance customer satisfaction through personalized shopping experiences. These innovations have improved both efficiency and sales conversion rates, a model other businesses can replicate to meet evolving customer expectations.

IBM’s Watson with Gen AI 

IBM is enhancing its Watson platform with generative AI capabilities designed for enterprise use. This includes new natural language processing tools that help businesses analyze feedback and streamline operations, demonstrating how custom generative AI solutions can seamlessly integrate with existing business systems. 

Gen AI’s Potential for Startups and SMBs 

The rise of Gen AI is not limited to large corporations. Many small and medium-sized businesses (SMBs) and startups across the USA are adopting Gen AI solutions, particularly in sectors like healthcare, finance, and retail. For SMBs, Gen AI offers opportunities to streamline processes and improve customer experiences, giving them a competitive edge. 

Key Strategies for SMBs 

1. Identify Targeted Use Cases 

SMBs should start by identifying specific applications of Gen AI, such as automating customer service or improving data analysis. 

2. Use Cloud-Based Solutions 

Cloud platforms provide cost-effective access to Gen AI tools, allowing SMBs to adopt without major infrastructure investment. 

3. Train Your Team 

Upskilling employees ensures effective use of Gen AI, maximizing its impact across business functions. 

4. Adopt a Data-Driven Approach 

High-quality data is essential for accurate AI predictions, so SMBs should establish robust data collection and management practices. 

For more insights on how generative AI can enhance your business, explore Performix’s resources on generative AI. 

[abdiyacaris]

Next-gen cybersecurity solutions and managed services

Next-gen cybersecurity solutions and managed services focus on advanced and proactive approaches to protecting digital assets, networks, and data. Here are some key areas where these modern cybersecurity solutions are evolving:

1. AI and Machine Learning (ML) Integration

Threat Detection and Response: AI and ML-driven systems can analyze network behavior and recognize patterns to identify anomalies in real-time, helping to prevent breaches before they occur.

Automated Incident Response: With AI, cybersecurity systems can automatically respond to potential threats, limiting the impact on the system.

Predictive Analysis: Machine learning models use historical data to predict and prevent emerging threats.

2. Zero Trust Architecture

Access Control: Zero Trust requires strict identity verification for every person and device, whether inside or outside the network, limiting potential damage from unauthorized access.

Microsegmentation: Networks are divided into segments with separate access controls, isolating threats if they breach the system perimeter.

3. Managed Detection and Response (MDR)

MDR services provide continuous monitoring and active threat hunting to detect, analyze, and mitigate threats in real-time.

Managed Security Services Providers (MSSPs) offer a cost-effective solution for businesses by handling complex cybersecurity requirements, allowing internal teams to focus on other areas.

4. Extended Detection and Response (XDR)

XDR solutions unify data across multiple security layers, like email, endpoints, servers, and networks, for enhanced visibility.

By integrating multiple data sources, XDR improves detection accuracy and provides deeper insights into threats, enhancing response capabilities.

5. Security Orchestration, Automation, and Response (SOAR)

SOAR platforms help manage security operations through automation, coordination, and analysis, making it easier to handle high volumes of security alerts.

With automated responses, SOAR reduces the time to react to incidents, improving overall security posture.

6. Cloud-Native Security Solutions

As businesses move to cloud environments, cloud-native security focuses on protecting data, workloads, and services hosted in the cloud.

Cloud Security Posture Management (CSPM) and Cloud Workload Protection Platforms (CWPP) are two tools for enhancing security within cloud infrastructures.

7. Identity and Access Management (IAM) with Multi-Factor Authentication (MFA)

IAM tools manage user permissions, enforce secure access controls, and prevent unauthorized access to critical resources.

MFA adds another layer of security by requiring multiple forms of verification, enhancing defenses against compromised credentials.

8. Endpoint Detection and Response (EDR) and Network Detection and Response (NDR)

EDR solutions monitor endpoint devices, identifying and mitigating malicious activities on each device.

NDR focuses on traffic moving through networks, helping detect unusual behaviors that might indicate threats.

9. Security Awareness Training and Phishing Simulation

Many managed services include employee training to mitigate social engineering risks.

Phishing simulations and ongoing education ensure employees recognize and avoid common threats.

These next-gen cybersecurity solutions and managed services are key to addressing increasingly sophisticated cyber threats, and they enable businesses to maintain robust defenses while optimizing resources and staying compliant with security standards.

[experiencespermile]

Next-Gen Mobility Transformation: Redefining the Journey with Mobility Transformation Solutions and Experiences per Mile

In today’s fast-paced world, the mobility landscape is transforming at an unprecedented rate. With the rise of new technologies, evolving customer expectations, and a shift towards sustainable solutions, the automotive industry focuses on delivering transport and experiences per mile (EPM). EPM redefines how we approach mobility, emphasizing comfort, connectivity, and personalization throughout the journey. Let’s explore how Next-Gen Mobility Transformation is reshaping the automotive and transport sectors and how Mobility Transformation Solutions are creating a more connected, sustainable future.

The Concept of Experiences per Mile (EPM)

Traditional mobility has been about getting from point A to point B, but next-gen mobility introduces the idea of enriching each mile with experiences that enhance the user journey. Experiences per mile focuses on improving passenger engagement, comfort, and satisfaction, transforming a simple commute into an immersive, enjoyable experience. This paradigm shift challenges automakers, service providers, and tech companies to go beyond the conventional by leveraging cutting-edge technologies like AI, IoT, and machine learning.

Key Features of Experiences per Mile (EPM):

Personalization: Using data insights, vehicles can adapt to individual preferences, creating a highly tailored experience for each passenger.

Seamless Connectivity: With advanced IoT integration, passengers can stay connected, access their favorite entertainment, or even work while on the go.

Enhanced Safety and Comfort: By integrating real-time feedback, sensors, and AI-based predictions, EPM elevates the in-vehicle safety and comfort experience.

To understand more about this, explore the resources provided by Experiences per Mile, a collaborative platform where industry experts share insights and advancements in the field of next-gen mobility.

Next-Gen Mobility Transformation Solutions

The shift toward next-gen mobility requires robust and innovative solutions. Here are some of the key technologies driving this transformation:

Connected Vehicles: Cars that communicate with each other and their surroundings enhance road safety, improve traffic management, and deliver real-time updates to drivers. This connectivity enables vehicles to “learn” from each journey, continuously optimizing the experience for each mile traveled.

Electrification and Sustainable Energy: Transitioning to electric vehicles (EVs) is a cornerstone of mobility transformation, offering sustainable energy solutions that reduce emissions and dependency on fossil fuels. This green revolution is reshaping urban transport systems, creating a cleaner, more sustainable future.

Autonomous Driving: Autonomous or self-driving vehicles represent the future of mobility, where advanced sensors and AI enable cars to navigate without human intervention. This development will make transportation more accessible, reduce accidents, and open up new ways to utilize time during travel.

Mobility-as-a-Service (MaaS): MaaS integrates various transport modes into a single, accessible platform, allowing users to book, pay for, and manage their journeys seamlessly. MaaS helps streamline mobility by enabling users to choose the most efficient and economical mode of transport for each leg of their journey.

How Mobility Transformation Solutions Support Experiences per Mile

Mobility Transformation Solutions are crucial in realizing the full potential of Experiences per Mile. These solutions emphasize creating seamless, personalized, and dynamic journeys.

1. Intelligent Transportation Systems (ITS): These systems help in managing road traffic, reducing congestion, and improving safety. By providing data-driven insights, ITS allows passengers to experience smoother and faster travel, contributing to the overall experience per mile.

2. Predictive Maintenance and Vehicle Health Monitoring: Leveraging data analytics, predictive maintenance minimizes breakdowns and optimizes performance. This ensures vehicles remain in optimal condition, offering a comfortable and safe journey.

3. AI-Based Passenger Interaction Systems: AI-driven systems enable passengers to interact with their vehicles in natural, intuitive ways, enhancing user experience. Voice-activated controls, personalized infotainment options, and real-time assistance transform vehicles into smart companions.

4. In-Vehicle Entertainment and Productivity Solutions: By integrating digital content and productivity tools, passengers can enjoy their journey through entertainment, stay connected with work, or even engage in learning activities during travel.

Transforming Mobility, One Mile at a Time

As mobility transformation solutions evolve, the way we interact with and experience travel is changing. Experiences per mile take this vision further, redefining journeys with next-gen mobility solutions that prioritize the passenger experience. With seamless integration of cutting-edge technology, these solutions are making journeys safer, more comfortable, and highly personalized.

The road to the future of transportation is paved with innovation, collaboration, and a commitment to a user-first approach. As next-gen mobility and experiences per mile take center stage, the journey will be as meaningful as the destination itself.

[frameoutlook]

How Are Telecoms Saving Millions on Network Operations and IT? These AI Use Cases Show You the Way

A recent study by McKinsey found that AI-driven automation in telecom operations could lead to a 25-30 % reduction in operational costs. This includes automating network planning, IT processes, and support functions, allowing companies to operate more efficiently and quickly. These improvements are becoming critical as telecom operators face growing pressure to roll out new technologies like 5G, maintain network performance, and reduce downtime. 

In this article, we'll look at how Gen AI is transforming two major areas in the telecom industry: optimizing network operations and speeding up IT processes through automation. By using AI-powered solutions, telecom companies can improve network planning, accelerate software development, and reduce technical debt, positioning themselves for future success in a competitive market. 

This move toward AI-driven operations goes beyond just improving efficiency—it's about reshaping how telecom operators manage their entire IT systems, enabling faster service delivery, lowering costs, and boosting customer satisfaction. 

Network Operations Optimization

Telecom networks are growing more complex with the rollout of technologies like 5G and IoT, making efficient network management a critical priority. Gen AI offers telecom companies new ways to optimize network operations, improve capital efficiency, and reduce operational costs. One of the most impactful areas where Gen AI is being deployed is in network mapping and planning, where it can analyze unstructured data, streamline maintenance schedules, and optimize network resource allocation. 

Network Mapping and Planning with Gen AI

Traditional network management relies heavily on manual processes and structured data analysis, which can be time-consuming and prone to human error. Gen AI, however, can process unstructured data such as supplier contracts, technical reports, and network component specifications to provide a comprehensive view of a network’s infrastructure. 

For instance, a European telecom operator used Gen AI to automate its network mapping processes, reducing the time required for network audits and assessments by 40%. By leveraging AI’s ability to analyze vast amounts of unstructured data, the operator was able to more accurately assess compatibility between network components, predict maintenance needs, and identify areas where operational planning could be improved. This level of insight is vital for preventing costly network outages and ensuring optimal performance during peak usage times.

Read More: https://www.frameoutlook.com/cxo-viewpoint/how-are-telecoms-saving-millions-on-network-operations-and-it-these-ai-use-cases-show-you-the-way-nid-671.html

[vtusoft]

Offshore Development Centers and SDLC AI Transforming Application Outsourcing by 2025

Introduction

With the rapid rise of globalization and digital transformation, companies are increasingly leveraging Offshore Development Centers (ODCs) and outsourced application support to maximize efficiency and reduce costs. As we approach 2025, businesses like V2Soft are tapping into the potential of SDLC AI and gen AI to drive scalable and agile development. In this blog, we’ll dive into the key aspects of ODC models, explore the advantages of Offshore Managed Services, and present forecasted statistics that reveal their impact on the software testing industry.

Understanding Offshore Development Centers and Their Role

An Offshore Development Center (ODC) acts as a strategic extension of a company's in-house team, often located in a low-cost region like India. These centers provide companies with dedicated resources focused on development, testing, and support services. For instance, V2Soft’s Offshore Development Center in India offers a wide range of digital solutions, from application outsourcing to ODC IT services.

What is ODC and Why Does it Matter?

An ODC is essentially a model that companies adopt to set up a remote team for various development tasks. The ODC model has evolved to become a preferred solution for organizations needing to balance quality with cost-efficiency. ODC Offshore Delivery Centers play a pivotal role in scaling business solutions, providing teams with access to global talent and technology.

Offshore Managed Services for Cost-Efficiency

Offshore Managed Services is a key component of the ODC model, offering support for processes that are essential but not core to an organization’s primary goals. By outsourcing these services to an ODC offshore development center, companies can ensure operational continuity while focusing on their core business objectives.

Forecast for 2025: Offshore Development Center Trends

Looking forward to 2025, studies show that the demand for ODC solutions is projected to grow by approximately 12% annually due to the increasing need for digital services. The ODC business solutions model is expected to drive down operational costs by up to 60% for companies using offshore teams.

Offshore Development Center Statistics for 2025:

ODC Technology usage is expected to increase by 18%, driven by advancements in SDLC AI and automation.

Offshore Digital Services from ODC companies in India are projected to account for 30% of outsourced IT services globally.

ODC IT Services demand will see a 10% annual growth, especially within sectors like finance, healthcare, and retail.

The Role of SDLC AI and Gen AI in ODC

SDLC AI (Software Development Life Cycle Artificial Intelligence) plays an essential role in enhancing the productivity and efficiency of ODC operations. By 2025, over 70% of ODCs are expected to integrate SDLC AI to streamline software testing and application support.

How SDLC Gen AI is Revolutionizing Testing and Application Support

SDLC Gen AI is paving the way for smarter testing and deployment processes. This technology enables teams to automate repetitive tasks and predict potential issues within the software testing life cycle. As ODC companies increasingly adopt gen AI for outsourced mobile testing and outsourced application support, they will be able to deliver high-quality solutions faster and more accurately.

Software Testing: The Future of Outsourcing and Consulting

V2Soft provides software testing consulting and outsourcing services that meet the dynamic needs of modern businesses. By 2025, software testing outsourcing solutions are expected to become essential components of ODC services, allowing businesses to achieve up to 40% time savings on testing processes. Furthermore, the adoption of software testing services web will streamline the integration of global testing services into existing applications, resulting in enhanced scalability.

Software Testing Forecasts for 2025:

Outsourced testing centers are expected to grow by 15% globally, with outsourced mobile testing gaining a larger share.

The software testing outsourcing solution market is projected to be worth $55 billion by 2025.

Outsourcing applications and testing are anticipated to reduce overall IT costs by 45% for companies employing a comprehensive outsourcing strategy.

ODCs in the USA and India: Comparative Advantages

While ODC companies in India dominate the offshore market, ODC companies in the USA offer closer collaboration opportunities with domestic firms. V2Soft’s ODC model enables clients to select from a variety of global ODC locations, ensuring a combination of time zone advantages, regional expertise, and cost-effective service delivery.

Benefits of ODCs in India:

Access to skilled professionals with extensive ODC technology expertise.

Significant cost advantages due to lower operational expenses.

Strategic location advantage for European and Asian markets.

Advantages of ODCs in the USA:

Proximity to North American clients, enhancing collaboration and reducing communication gaps.

High security and compliance standards for sensitive data.

Flexibility to scale teams based on project needs with ODC business solutions.

The Growing Importance of ODC and Outsourced Testing Centers

Offshore Testing Centers are increasingly integral to software development as companies rely on them to ensure that applications meet global quality standards. These centers, often part of an ODC, provide a robust framework for outsourced application and mobile testing, allowing businesses to leverage automated tools and advanced testing protocols.

How ODC Services Enhance Software Quality

ODC Services not only provide skilled resources but also offer tailored solutions that cater to specific client needs. For instance, V2Soft’s outsourced testing center solutions enable clients to execute testing activities within secure, scalable environments. This approach helps businesses to reduce testing timelines and improve application quality.

Conclusion

As businesses expand their reliance on Offshore Development Centers and outsourced application support, the role of ODC technology and SDLC AI in driving efficient, cost-effective development solutions is only expected to grow. By 2025, companies like V2Soft will continue to pioneer new standards in ODC services, outsourced testing, and software testing outsourcing solutions that align with evolving market demands. Embracing these offshore and outsourced solutions enables organizations to remain competitive, agile, and future-ready in an ever-evolving tech landscape.

[pipelineprosblog]

Optimizing Lead Generation with CLICKVISION: Unlocking the Future of Effective Business Growth

In today’s fast-paced digital landscape, businesses are constantly searching for innovative strategies to acquire high-quality leads. Lead generation has become a pivotal component of every marketing strategy, especially for companies striving to expand their reach and grow sustainably. With an increasing number of tools and techniques available, businesses are faced with the challenge of finding the right solution that fits their goals. One such solution that stands out is CLICKVISION, a leading name in modern lead generation. Through cutting-edge technology and a focus on precision targeting, CLICKVISION Lead Gen is quickly becoming a game-changer in the world of customer acquisition.

What is Lead Generation?

Before diving into the intricacies of CLICKVISION’s approach, it’s important to understand the core concept of lead generation. Lead generation refers to the process of identifying and attracting potential customers for a business’s products or services. It involves a series of marketing activities designed to capture attention, gather contact information, and nurture relationships until the prospect is ready to make a purchasing decision.

Traditionally, lead generation has been about casting a wide net and hoping to catch a few high-quality leads. However, with the rise of digital marketing, the focus has shifted to more strategic, targeted efforts. Today, businesses use a variety of methods including content marketing, email campaigns, social media outreach, and paid advertisements to generate leads effectively.

Why is Lead Generation Crucial for Business Success?

Effective lead generation is no longer a luxury; it’s a necessity for sustained business success. Here are a few reasons why lead generation should be a priority for companies:

Scalable Growth: Proper lead generation ensures that businesses can expand without hitting growth bottlenecks. By continually attracting new prospects, a business can maintain momentum.

Cost Efficiency: With targeted lead generation, companies can allocate resources more effectively. Rather than spending on broad, untargeted campaigns, businesses can focus on high-potential leads.

Build Relationships: Lead generation is not just about converting prospects into customers; it’s about building long-term relationships. By understanding customer needs and providing value through each stage of the journey, businesses can foster loyalty.

CLICKVISION Lead Gen: A New Standard in Lead Generation

CLICKVISION has introduced a transformative approach to lead generation. Through its unique methods and technology, the company has redefined how businesses approach their lead generation strategies.

Here’s what sets CLICKVISION apart:

1. Precision Targeting

CLICKVISION Lead Gen utilizes advanced data analytics and AI to help businesses target the right audience. By analyzing customer behaviors, interests, and buying patterns, it ensures that every lead is a potential high-quality prospect. Unlike traditional methods, which often cast a wide net, CLICKVISION’s approach is focused, saving businesses time and resources while ensuring a higher conversion rate.

2. Automation and Efficiency

Automation has become a key element of modern lead generation strategies. CLICKVISION automates much of the process, reducing manual work and accelerating the lead acquisition cycle. From lead capture forms to follow-up emails, automation allows businesses to manage leads efficiently, ensuring that no prospect slips through the cracks.

With CLICKVISION, businesses can maintain a steady flow of leads without constant manual intervention. This not only saves time but also allows teams to focus on more strategic tasks, such as closing deals and improving customer engagement.

3. Multichannel Integration

In today’s world, lead generation doesn’t happen through a single channel. Prospects engage with businesses across multiple platforms, including social media, websites, email, and more. CLICKVISION Lead Gen takes a multichannel approach, integrating various platforms into one unified strategy. This integration ensures that businesses can reach prospects wherever they are, increasing the chances of generating high-quality leads.

4. Real-Time Analytics

CLICKVISION’s robust analytics system provides businesses with real-time insights into their lead generation efforts. These insights allow companies to adjust strategies quickly and effectively, ensuring that marketing campaigns remain on track. By tracking key metrics such as lead conversion rates, click-through rates, and audience engagement, businesses can make data-driven decisions that improve overall lead generation performance.

5. Personalized Experience

Personalization is one of the most powerful tools in modern marketing. CLICKVISION Lead Gen leverages data to create personalized experiences for each lead, ensuring that every interaction feels relevant and valuable. By tailoring content and offers to individual prospects, businesses can increase the likelihood of conversion and build stronger relationships over time.

The Impact of CLICKVISION on Lead Generation

CLICKVISION’s innovative approach to lead generation has helped countless businesses improve their lead acquisition processes and, in turn, their bottom line. According to recent industry studies, companies that implement advanced lead generation techniques, like those offered by CLICKVISION, see:

Higher Conversion Rates: By targeting high-quality leads and providing a personalized experience, businesses can see an increase in conversion rates.

Improved ROI: With more efficient and effective lead generation efforts, businesses experience a better return on investment (ROI) for their marketing budgets.

Stronger Customer Relationships: By using automation and real-time analytics, businesses can nurture leads more effectively, leading to stronger and longer-lasting customer relationships.

Best Practices for Implementing CLICKVISION Lead Gen

While CLICKVISION offers powerful tools and resources, the success of a lead generation strategy also depends on how it’s implemented. Here are a few best practices to ensure businesses maximize the benefits of CLICKVISION Lead Gen:

Understand Your Target Audience: Use data and analytics to understand your customers’ behaviors, needs, and pain points. This information will help you create more targeted and personalized lead generation strategies.

Optimize Your Landing Pages: Ensure that your landing pages are optimized for conversion. A clean design, clear call-to-action (CTA), and compelling content can significantly improve lead capture rates.

Monitor and Adjust: Regularly monitor your campaigns to see what’s working and what isn’t. CLICKVISION’s real-time analytics will help you make adjustments and optimize performance.

Conclusion

Lead generation is a critical component of any business’s growth strategy. As businesses continue to face increasing competition and demand for high-quality leads, platforms like CLICKVISION Lead Gen offer a unique opportunity to stay ahead of the curve. Through precision targeting, automation, multichannel integration, and real-time analytics, CLICKVISION is revolutionizing the way businesses acquire and nurture leads. By adopting best practices and leveraging cutting-edge technology, businesses can not only improve their lead generation efforts but also achieve long-term success in today’s competitive market.

Incorporating innovative tools such as CLICKVISION Lead Gen into your marketing strategy can help transform your lead generation efforts, ensuring you’re not only reaching the right prospects but converting them into loyal customers. The future of lead generation is here, and it’s powered by intelligent, data-driven solutions.

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NVIDIA MGX And Intel Xeon Powered DC-MHS Servers At SC24

MSI, a leading global provider of high-performance server solutions, displayed its AI server based on the NVIDIA MGX architecture and DC-MHS server portfolio powered by Intel Xeon 6 processors at booth 3655 at Supercomputing 2024 (SC24) from November 19–21 MSI’s most recent products are made with the goal of optimising compute density, energy efficiency, and modular flexibility in order to meet the demanding requirements of AI, HPC, and data-intensive applications. MSI provides the scalable performance and resilience required for data centres to keep up with changing HPC demands with its Intel Xeon 6 DC-MHS servers, which are designed on a flexible DC-MHS architecture.

NVIDIA MGX Server for Next-Gen AI

With its two Intel Xeon 6 CPUs and eight FHFL dual width GPU slots, MSI’s CG480-S5063 AI server, which is based on the MGX architecture, is specifically designed to meet the high needs of AI. It supports the potent NVIDIA H200 NVL GPUs, which enable enormous parallel processing for workloads related to AI, LLM, and data analytics. High throughput for data-intensive applications is provided by its 20 PCIe 5.0 E1.S NVMe bays and 32 DDR5 DIMM slots, while PCIe 5.0 x16 slots allow for flexible and fast network integration. For AI systems that prioritize optimal computational efficiency and scalability, this 4U server provides the performance and scalability required.

Intel Xeon 6 DC-MHS Servers Solutions for HPC Data Centers

High-performance data center and HPC environments benefit from unparalleled scalability and flexibility with MSI’s Intel Xeon 6 processor-based DC-MHS servers and server motherboards. Microsoft’s solutions provide optimal resource allocation across a variety of applications with Intel Xeon 6 processors, which have P-cores for optimal performance and E-cores for energy-efficient operations under heavy workloads.

Data centers can effectively scale and swiftly adjust to the ever-increasing demands of AI, analytics, and intensive computing workloads with these DC-MHS solutions, which were designed with efficient thermal management and modularity in mind. They use Extended Volume Air Cooling (EVAC) CPU heatsinks to maintain stable operation even under intense use. These solutions, which combine the potent Intel Xeon 6 processors with the flexible DC-MHS architecture, give data centers the tools they need to remain competitive in the quickly changing HPC market of today.

DC-MHS Servers

Intel Xeon 6 processors, DDR5 DIMM slots, and broad PCIe 5.0 compatibility enable MSI DC-MHS servers to provide unparalleled computational density and modular scalability. These platforms, which are based on the OCP DC-MHS architecture, offer data centers the adaptability, strength, and efficiency they need to succeed in demanding HPC and AI environments. They include DC-SCM2 server management modules with A speed AST2600 BMC support and improved front I/O design.

For demanding computation and memory-bound workloads in HPC environments, the CD270-S3061-X2 is a 2U, two-node server. The system offers significant processing power and memory bandwidth necessary for parallel tasks,with its single Intel Xeon 6 CPU with up to 350W TDP and 16 DDR5 DIMM slots per node. High-speed data access is made possible by its six PCIe 5.0 x4 U.2 NVMe bays per node, which makes it perfect for high-performance and scalable data center architecture.

The CX270-S5062 is a 2U server with 32 DDR5 DIMM slots and dual-socket Intel Xeon 6 processors with a maximum TDP of 350W each that is designed for maximum computation throughput. This device facilitates quick data processing and AI-driven calculations by supporting up to 24 PCIe 5.0 x4 U.2 NVMe bays and dual GPU options to offer both large storage and GPU acceleration capabilities.

A single Intel Xeon 6 processor with a maximum TDP of 350W powers the CX271-S3066, a 2U server that offers balanced performance and scalability. This server, which supports up to 24 PCIe 5.0 x4 U.2 NVMe bays and 16 DDR5 DIMM slots, is designed for data-centric applications that need quick access to data and effective processing, guaranteeing that data centers can quickly meet the demands of AI and HPC.

DC-MHS Server Motherboards

The latest Intel Xeon 6 processors with P-cores and E-cores power the full-width M-FLW and density-optimized M-DNO (Type-4, Type-2) motherboards in the MSI DC-MHS series, which offers optimal performance and energy efficiency for a range of compute-intensive applications. These motherboards offer the processing power and scalability required for sophisticated AI, data analytics, and HPC applications with their DDR5 memory slots, fast PCIe 5.0 connectivity, and flexible I/O options.

A single Intel Xeon 6 CPU, up to 500W TDP, and 12 DDR5 DIMM slots are supported by the D3071 M-DNO Type-2 HPM.

32 DDR5 DIMM slots, up to 350W TDP, and dual Intel Xeon 6 CPUs are supported by the D5062 M-FLW HPM.

The D3066 M-DNO Type-4 HPM has 16 DDR5 DIMM slots, a single Intel Xeon 6 processor, and a maximum TDP of 350W.

The D3061 M-DNO Type-2 HPM has 12 DDR5 DIMM slots, a single Intel Xeon 6 processor, and a maximum TDP of 350W.

The OCP DC-SCM v2.0-compliant MGT1 DC-SCM2 Module facilitates cross-platform use, lowers deployment and maintenance expenses, and streamlines testing and validation.

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