#gpt store update

[reallytoosublime]

Welcome to the GPT Store, where innovation meets imagination! Nestled within the bustling heart of the digital marketplace, the GPT Store stands as a beacon of cutting-edge technology and limitless creativity. As you step into our virtual emporium, prepare to embark on an extraordinary journey through the realms of artificial intelligence and linguistic prowess.

With its sleek interface and intuitive design, the GPT Store offers a seamless shopping experience like no other. Whether you're a seasoned developer, a curious enthusiast, or an avid explorer of the digital frontier, there's something here for everyone. From advanced AI models to bespoke language tools, our vast collection caters to a diverse array of needs and interests.

At the heart of the GPT Store lies our flagship product: the renowned GPT series. Powered by state-of-the-art deep learning algorithms and trained on vast swathes of data, these AI models represent the pinnacle of natural language processing. Whether you seek assistance with writing, coding, or creative endeavors, our GPT models are your ultimate companions in unlocking new possibilities.

But the GPT Store is more than just a repository of AI models. It's a vibrant marketplace where ideas flourish and innovation thrives. Browse through our curated selection of plugins, extensions, and add-ons, each crafted to enhance your AI experience. From language translation tools to sentiment analysis plugins, these resources are designed to augment your productivity and unleash your creativity.

So, whether you're a seasoned AI aficionado or a curious newcomer, come discover the wonders of the GPT Store. Unleash your imagination, explore the limitless potential of artificial intelligence, and embark on a journey that transcends the boundaries of what's possible. Welcome to the future of innovation.

GPT Store: How To Use and Make Money Online 2024

[youtubemarketing1234]

Welcome to the GPT Store, where innovation meets imagination! Nestled within the bustling heart of the digital marketplace, the GPT Store stands as a beacon of cutting-edge technology and limitless creativity. As you step into our virtual emporium, prepare to embark on an extraordinary journey through the realms of artificial intelligence and linguistic prowess.

With its sleek interface and intuitive design, the GPT Store offers a seamless shopping experience like no other. Whether you're a seasoned developer, a curious enthusiast, or an avid explorer of the digital frontier, there's something here for everyone. From advanced AI models to bespoke language tools, our vast collection caters to a diverse array of needs and interests.

At the heart of the GPT Store lies our flagship product: the renowned GPT series. Powered by state-of-the-art deep learning algorithms and trained on vast swathes of data, these AI models represent the pinnacle of natural language processing. Whether you seek assistance with writing, coding, or creative endeavors, our GPT models are your ultimate companions in unlocking new possibilities.

But the GPT Store is more than just a repository of AI models. It's a vibrant marketplace where ideas flourish and innovation thrives. Browse through our curated selection of plugins, extensions, and add-ons, each crafted to enhance your AI experience. From language translation tools to sentiment analysis plugins, these resources are designed to augment your productivity and unleash your creativity.

For those seeking personalized solutions, the GPT Store offers bespoke services tailored to your specific requirements. Whether you need custom model training, API integration, or specialized consultancy, our team of experts is here to help you realize your vision. With their unparalleled expertise and dedication to excellence, they'll guide you every step of the way, ensuring that your AI journey is both rewarding and transformative.

GPT Store: How To Use and Make Money Online 2024

[chainteeth1218]

dearest tumblr,

life is changing. lots has shifted in the past month or two, but none the less i am loving the partying and bonding with my baddies as usual. still living it up and dancing to charli xcx at least once a week. i’ve been meeting many new and wonderful people have thoroughly enjoyed and laughing and smiling with all of them. as well as plotting on possible future hoes. autumn is fast approaching but i am accepting this new season with open arms, the leaves are beginning to fall and i am excited to see what the next 3 months have in store for me. last week i asked chat gpt why my ex doesn’t want me back. clearly not my strongest moment. anyways, i just wanted to update all my dear tumblr followers (its just chloe) and let you all know that through all my hardships i am doing well and still in fact bumpin that. and will continue to do so. much love

[darkietrashcan]

CHAT GPT analyzes Bakudeku & Bakugo's development

So I've been fooling around with ChatGPT, and decided to update the AI with the recent events that have happened in the manga.

(Manga spoilers until ch.362! BEWARE!)

Let me clarify that CHAT GPT has been programmed to having stored worldwide information until September 2021. I will only show the juciest replies I got from the AI, but let me clarify that I successfully updated the AI to understand what had happened in the manga until now (as of 5th April 2023).

(ChatGPT stores information given in the chat, and is capable to learn about that info and reproduce it later on during the conversation if needed.)

Let's start!

The following reply came when I asked ChatGPT if it was fair for fans to like Bakugo given his development, and if the AI agreed with me that Bakugo was well written:

(About the fairness of liking Bakugo: everyone is entitled to their own opinions, ok? But this question rooted from a discussion I had with a few IRL's who told me I was crazy for liking Bakugo. So yeah, personal reasons, but still, I wanted to show you the answer!)

I really liked the response lol, it's pretty well thought and comprehensive. It's scary how much an AI can learn and give you these kind of responses in such a short amount of time.

Another one: I asked the AI about what they thought about the likeliness of bkdk ending up canon.

(I'm not surprised by the answer. Dunno what y'all think about this but sounds pretty fair to me. However, that's just my opinion. I'd love bkdk to end up canon, though. Crossing my fingers.)

But then I asked the AI what they thought that bkdk still needed in order to become canon:

That was all. I don't agree much. But well, that's my opinion.

Next one: I asked the AI about the meaning of Bakugo's death relating it to bakugo's and deku's relationship. NOTE THAT UNTIL THEN, I DID NOT TELL THE AI ABOUT BAKUGO'S EVENTUAL REVIVAL AND DEKU'S REACTION TO IT! (Y'know, the "control your heart" part)

Then, I added the context that the AI lacked, and their response was...

Even though it's obvious, this response hyped me up for Bakugos revival and him stepping up to assist Deku during the fight against Shigaraki! Or maybe in another moment, whenever Hori chooses it'd be right to fit Bakugo in the narrative.

That's all! It's been pretty fun to chat with the AI, lol. Took me around 1h30 minutes, but totally worth it.

Note that the AI, although offering objective analysis' of the context I gave them, provided responses that, most of the time, I agreed with. Which lead me to think that, if I'm a very subjective bkdk shipper, I could turn this AI into a bkdk shipper too, lol, If I had more time and willingness to convince them. My take here is, that antis could get responses matching their opinions as well. So yeah, please, do not take these answers as enunciations from the Holy Bible, but just some screenshot about a crazy fan fooling around with an AI app because she's bored and doesn't wanna do UNI work. Anyway, hope that you enjoyed reading these answers. If you want me to ask the AI about more specific things, tell me! Might do another post like this one in the future!

[maiosx]

my hackintosh journey

formatting usb's to a gpt partition without gibmacOS's python script (only on windows with the bat cmd launcher script) was a pain for about a day or two and I wasn't aware it existed until I found it and it's still broken write to usb command is unavailable because the download server is off so writing the OS dmg images required transmac and that's if you can even find a proper installer. I also realized I was copying the ventura mac installer incorrectly to the drive then figured I should just boot efi's in a seperate usb drive to solve partitioning or read/write issues. My config.plist file had many things inaccurate and proper tree manager and ocat auxilary tools don't come with manuals. After finding a proper coffee-lake efi without any model identifiers, I used OCAT to generate an SMBIOS of iMac 19,1 and proper tree to edit some values like securebootmodel to disabled and enablewriteunprotector to true then rebuilt it, saved and pasted some prebuilt ACPI SSDTs then rebuilt the config file again. This is all after the original high sierra install which needed a proper clover EFI so I had used the one I found from AIO Clover Boot method's img file off an abandoned blog. Once I had High Sierra running I used a script from tonymacx86 to install web drivers for the OS but it broke for some reason after many reboots of the ventura installer. So I had to then update the OS and then installed the original web driver from nvidia. After that installation, you are required to use opencore's legacy patcher to build the new OS usb or off the app store with the dd to usb terminal command but opencore's method is easier. My take is... If you want to be able to run mac OS X on a PC just buy one. KVM's on Qemu with linux using Sosumi are outdated, they don't support usb passthrough correctly if you don't have the USB Kext installed for your mobo or Qemu updated and set up with virt-manager which is some other nonsense of it's own. The whole thing is a mess all over the internet without any proper guide to complete it all in 2023. That's even after you figure you can run the legacy patcher's root patch for GPUs - says it runs on ventura but I didn't test it and without metal app support.. and you still need to know the secret boot arguments for your GPU if it's not AMD based and you'll likely get some Invalid X symbol at the second boot for not disabling system integrity protection while rooting or not copying over the EFI bc I don't even know how to safe boot to a hackintosh for turning off SIP if it doesn't boot in the first place. I will stay on Windows 10 and keep my High Sierra installation though because old software is kinda neat, less broken, and faster than whatever is out in the wild. Manjaro Linux running gnome on the other hand, or Fedora are really good for running servers without needing windows license keys and it's probably why sysadmins like linux so much tho the other software on it mostly sucks and so without maiOSX running on edge and all the web apps it's toast and the safari developer thingy on iOS doesn't work on high sierra unless you update iTunes probably which is a security update of 2gb that will break the GPU again.. it's just awful how de-constructing updates and things are on all those mac OSes are. ventura looked neat though but, too grey for me. not dark enough.

[1256986]

What is Generative Engine Optimization (GEO) and How It’s Changing Digital Marketing

One of the latest trends that is making waves in the industry is Generative Engine Optimization (GEO). But what exactly does it mean, and how is it changing the way businesses approach online marketing? Let’s break it down in simple terms.

What is Generative Engine Optimization (GEO)?

Generative Engine Optimization is a new strategy that infuses the power of traditional SEO with generative AI. It focuses on improving content creation, optimization, and delivery to search engines and users. In other words, it makes websites and digital content work better in search results because of AI tools that will create high-quality, relevant, and engaging content corresponding to what people are actually searching for.

Let’s take a closer look at the key parts of GEO:

Generative AI: AI models, for instance GPT-4 could create text and even generate images and videos. The data and patterns are taken in by the AI model; this is a text generator that can write content or captions that sound human, relevant to the topic presented.

Search Engine Optimization (SEO): SEO is the practice of improving your website so it ranks higher in search engine results like Google. The better your SEO, the more likely it is that people will find your website when they search for related keywords.

Generative Engine Optimization This takes the process of SEO one step further by including AI- based content specifically intended to help them rank better on search engines and reach potential customers. As opposed to creating original content, businesses can depend on AI to provide new optimized pieces of content on an enormous scale, and it gets easier and faster to reach more potential customers.

How GEO is Changing Digital Marketing

Faster Content Creation

One of the biggest challenges of digital marketing is being able to churn out high-quality content fresh off the stove daily. It's not that easy with the methods traditionally applied in that creating blog posts, social media updates, and other content types requires much time and effort to execute. That is what generative AI is for.

AI tools can produce content fast and relevant to a particular topic. It could easily optimize the same for search engines. For example, if a business wanted to create articles about their product, a few clicks using GEO tools will automatically create blog post or descriptions that are in line with popular searches. The latter will keep the businesses' websites fresh with new content, which is one of the most crucial factors of success for SEO.

Why It Works: This increases the speed of content creation, which means so businesses can create more content without adding more workload. The better the content is, the more probable your ranking on the search engine will be.

Example: An e-commerce store selling outdoor gear may generate this based on the help of artificial intelligence when all the product descriptions and blog post items regarding camping tips can be SEO-optimized and scored in search engines.

Better Personalization

This does not mean merely churning out good content; it will also enable businesses to formulate targeted marketing communications. Generative AI could use data involving customer behavior, search trends, and many other things, to make content that actually addresses the specific audience group. This is going to lead to more personalized experiences for consumers of this information type and should translate to higher engagement and conversion rates.

Why It Works: Almost all being a key driver of customer satisfaction, is a major guest to personalization. Giving businesses the ability to deliver content that fits the needs and interests of the user allows their audience to build a stronger connection with the business and to ultimately sell the product.

Example: Using AI, an online clothing store can create personalized email campaigns or product recommendations for customers and create a better chance of generating a sale.

Improved Search Engine Rankings

Basically, GEO is focused on optimizing SEO performance with the help of a generative AI. Businesses can create all kinds of content with related interests in accordance with search trends; moreover, this GEO has the potential to deliver improvements in keyword targeting, readability, and user engagement. Thus, GEO tools are specifically developed for optimizing content in a way that helps ranking on both search engines - like Google-and users.

Why It Works: Instead, the content from GEO may actually rank well in the search results with good quality matched for the intent of the users. It could now use its keywords to optimize its content while keeping it engaging and value-creating to the readers.

Example:A local restaurant could use AI to create SEO-optimized blog posts or landing pages focusing on the theme, such as best vegan restaurants in [city] or most affordable dining in [city]. Those then show up in the local search results. That attracts more potential customers to the restaurant.

Cost Efficiency and Scalability

Scaling content, large volume SEO-optimized content creation has long been an expensive affair; meaning large numbers of writers or content creators were required. GEO allows businesses to now use AI for the purpose of scaling content production without breaking the bank. Smaller businesses with minimal budgets can now leverage great chunks of information churned out in less time to outdo larger competitors.

Why It Works: AI is cost efficient as it eliminates the need for hand written or content produced. This allows businesses to mass produce content without paying a quality cost.

Example: AI is cost efficient as it eliminates the need for hand written or content produced. This allows businesses to mass produce content without paying a quality cost.

Improved User Experience

At the end of the day, for both search engines and businesses, it is about user experience, first. In the case of search engines like Google, the ultimate goal is to generate the best results for users; whenever a site has some good content that answers people's questions or gives any value, the more it will rank. Generative Engine Optimization helps businesses create relevant, engaging, and informative content that will support the user experience.

Why It Works: Generating the type of content, which identifies user needs, and is structured to be easily readable improves the overall experience that people have when coming to a website; they are likely to stay longer, and thus, it enables the people coming to the website to take the desired actions, whether signing-up or making a purchase.

Example: With the health and wellness brand through GEO, articles can be made to be well-structured, useful, and will answer common questions that most ask about health.

GEO and the Future of Digital Marketing

It's only a matter of time before Generative Engine Optimization unfolds more possible capabilities, including much more sophisticated tools that will generate content but might also optimize voice search, video, and so on.

Why It Matters: Here are the reasons why: first, businesses will have an early mover advantage with faster production of content at a better quality, with better SEO performance. What really plays the game of changing how businesses of any scale scale their efforts and stay ahead of the digital curve is to integrate AI into digital marketing.

Conclusion

With GEO, or generative engine optimization, AI is being used to combine with SEO to help businesses create higher-value, more relevant content that ranks well in searches and improves user experience. Which, while changing the game, promises to attract new customers toward any small business or large company, as it provides better, faster, and far more efficient techniques for creating content?

As AI technology becomes more advanced, companies using GEO will be able to take the lead in their industries, since GEO is an essential strategy of the future of digital marketing. Visit Eloiacs to find more about Digital Marketing.

[govindhtech]

Microsoft Azure OpenAI Data Zones And What’s New In Azure AI

Announcing the most recent Azure AI developments and the availability of Azure OpenAI Data Zones

Microsoft Azure AI is used by more than 60,000 clients, such as AT&T, H&R Block, Volvo, Grammarly, Harvey, Leya, and others, to propel AI transformation. The increasing use of AI in various sectors and by both small and large enterprises excites us. The latest features in Azure AI’s portfolio that offer more options and flexibility for developing and scaling AI applications are compiled in this blog. Important updates consist of:

There are Azure OpenAI Data Zones available for the US and EU that provide more extensive deployment choices.

Prompt Caching is available, Azure OpenAI Service Batch API is generally available, token generation has a 99% SLA, model prices are reduced by 50% through Provisioned Global, and lower deployment minimums are required for Provisioned Global GPT-4o models in order to scale effectively and minimize expenses.

Mistral’s Ministral 3B tiny model, Cohere Embed 3’s new healthcare industry models, and the Phi 3.5 family’s improved general availability offer more options and flexibility.

To speed up AI development, switch from GitHub Models to Azure AI model inference API and make AI app templates available.

Safely develop new enterprise-ready functionalities with AI.

United States and European Union Azure OpenAI Data Zones

Microsoft is presenting Azure OpenAI Data Zones, a new deployment option that gives businesses even more freedom and control over their residency and data privacy requirements. Data Zones, which are specifically designed for businesses in the US and the EU, enable clients to process and store their data inside predetermined geographic bounds, guaranteeing adherence to local data residency regulations while preserving peak performance. Data Zones, which cover several regions within these areas, provide a balance between the control of regional deployments and the cost-effectiveness of global deployments, facilitating enterprise management of AI applications without compromising speed or security.

By providing a solution that enables higher throughput and faster access to the newest AI models, including the most recent innovation from Azure OpenAI Service, this new feature streamlines the frequently difficult chore of maintaining data residency. Now, businesses can safely scale their AI solutions while adhering to strict data residency regulations by utilizing Azure’s strong infrastructure. Data Zones will soon be available for Provisioned and Standard (PayGo).

Updates for Azure OpenAI Services

Microsoft declared the Azure OpenAI Batch API for Global deployments to be generally available earlier this month. Using a separate quota, a 24-hour return time, and 50% less cost than Standard Global, developers can more effectively handle large-scale and high-volume processing activities using Azure OpenAI Batch API. One McKesson company, Ontada, is already using Batch API to process massive amounts of patient data from US oncology hospitals in an economical and efficient manner.

Additionally, it has enabled Prompt Caching on Azure OpenAI Service for the o1-preview, o1-mini, GPT-4o, and GPT-4o-mini models. By reusing recently viewed input tokens, developers can save expenses and latency with Prompt Caching. Applications that frequently employ the same context, like code editing or lengthy chatbot interactions, will find this capability especially helpful. Faster processing times and a 50% discount on cached input tokens for Standard offerings are provided by Prompt Caching.

It is reducing the basic deployment quantity for GPT-4o models to 15 Provisioned Throughput Units (PTUs) with further increments of 5 PTUs for the Provisioned Global deployment offering. To increase access to Azure OpenAI Service, it is also reducing the cost of Provisioned Global Hourly by 50%.

Microsoft is also launching a service level agreement (SLA) for token generation with a 99% latency. Especially at high volumes, this latency SLA guarantees that tokens are issued more quickly and reliably.

Customization and new models

With the addition of new models to the model library, it keeps broadening the selection of models. This month, it has several new models available, including models from Mistral and Cohere as well as models from the healthcare sector. Additionally, it is revealing that the Phi-3.5 family of models can be customized.

Advanced multimodal medical imaging models, such as MedImageInsight for image analysis, MedImageParse for image segmentation across imaging modalities, and CXRReportGen for detailed structured report generation, are part of the healthcare sector models. These models, which were created in partnership with Microsoft Research and industry partners, are intended to be adjusted and tailored by healthcare institutions to suit particular requirements, lowering the amount of data and processing power normally required to create such models from the ground up.

Mistral AI’s Ministral 3B: Ministral 3B, which emphasizes knowledge, commonsense thinking, function-calling, and efficiency, is a notable breakthrough in the sub-10B category. These models are designed for a wide range of applications, from creating specialized task workers to coordinating agentic processes, and they support up to 128k context length. Ministral 3B is a useful bridge for function-calling in multi-step agentic workflows when combined with bigger language models such as Mistral Large.

Cohere Embed 3: Embed 3, the multimodal AI search model that leads the market, is now accessible in the Azure AI Model Catalog! By enabling businesses to explore and analyze their massive volumes of data in any format, Embed 3’s capability to create embeddings from both text and images unlocks substantial value. This update transforms how companies navigate through complex materials like reports, product catalogs, and design files, positioning Embed 3 as the most potent and capable multimodal embedding model available.

Fine-tuning the Phi 3.5 family’s general availability, including Phi-3.5-mini and Phi-3.5-MoE: Phi family models can be easily customized to enhance basic model performance in a range of situations, including learning a new task or skill or improving response quality and consistency. When compared to models of the same size or next size up, Phi-3.5 models provide a more affordable and sustainable option because to their modest computing footprint and interoperability with cloud and edge. The Phi-3.5 family is already being adopted for non-connected scenarios and edge reasoning use cases. Today, developers may refine Phi-3.5-mini and Phi-3.5-MoE by utilizing serverless endpoints and the model as a platform offering.

Development of AI apps

Azure AI is being developed as an open, modular platform to enable developers to swiftly go from concept to code to cloud. Through the Azure AI model inference API, developers can now easily explore and access Azure AI models through the GitHub Marketplace. When developers are ready to customize and deploy, they can easily set up and log in to their Azure account to scale from free token usage to paid endpoints with enterprise-level security and monitoring without making any changes to the code. Developers can test out various models and compare model performance in the playground for free (usage limits apply).

In order to expedite the development of AI apps, it has unveiled AI App Templates. These templates are available to developers in Visual Studio, VS Code, and GitHub Codespaces. With a range of models, frameworks, languages, and solutions from vendors including Arize, LangChain, LlamaIndex, and Pinecone, the templates enable versatility. Developers can start with components or launch entire programs, allocating resources across Azure and partner services.

With these enhancements, developers can confidently scale AI systems, select the deployment choice that best suits their needs, and get started in their preferred environment immediately.

New tools to create enterprise-ready, safe AI applications

At Microsoft, its goal is to assist clients in using and developing trustworthy AI that is, AI that is private, secure, and safe. It is presenting two new features today that will help you confidently develop and grow AI solutions.

More than 1,700 models are available for developers to examine, assess, modify, and implement in the Azure AI model library. Although this wide range of options fosters creativity and adaptability, it can also pose serious difficulties for businesses that wish to make sure all implemented models meet their internal guidelines, security requirements, and legal requirements. Model selection and governance procedures can now be made simpler for Azure AI administrators by using Azure rules to pre-approve specific models for deployment from the Azure AI model catalog.

A comprehensive guide makes it easier to create custom policies for Azure OpenAI Service and other AI services, while pre-built policies for Models-as-a-Service (MaaS) and Models-as-a-Platform (MaaP) deployments are also included. When combined, these guidelines offer comprehensive protection for establishing an approved model list and implementing it throughout Azure AI Studio and Azure Machine Learning.

Developers may require access to on-premises resources or even resources not supported by private endpoints but nonetheless present in their custom Azure virtual network (VNET) in order to create models and applications. A load balancer called Application Gateway bases its routing choices on an HTTPS request’s URL. Using the HTTP or HTTPs protocol, Application Gateway will enable a private connection from the managed VNET to any resources.

It has been confirmed to enable private connections to Snowflake Database, Jfrog Artifactory, and Private APIs as of right now. Developers may access on-premises or bespoke VNET resources for their training, fine-tuning, and inferencing scenarios without sacrificing their security posture using Application Gateway in Azure Machine Learning and Azure AI Studio is currently available for public preview.

Read more on Govindhtech.com

[creativesgenie]

AI Marketing Trends to Watch in 2024 and 2025

AI (artificial intelligence) is making itself a place in every digital field. Allowing great versatility, AI is now becoming popular in the marketing industry. Since AI can manage detailed routine tasks efficiently and quickly, it lets marketers take time off and focus on more important things regarding their online business. 

But this makes many wonder about the future of AI in marketing. Many AI marketing tools have emerged in the last few years, and several continue to submerge in the digital landscape, pushing new possibilities for AI marketing trends. 

AI has already been integrated into many online businesses, but here are the most significant trends set to transform the marketing landscape with artificial intelligence in 2024 and the coming years:

Generative AI for Personalization

Generative AI has drastically improved the way marketers and traders interact with their clients by creating diverse content and personalizing their experiences. In the next year, we expect to see a rise in AI tools producing targeted, customized advertisements, content, videos, and posts, allowing customers to feel seen and heard, getting their needs met more appropriately. 

Other than that, AI can help with content optimization for maximum engagement and enhancing conversions. Plus, AI as a chatbot can help with personalized messaging allowing customers to feel understood at a more intimate level. 

Augmented Reality 

Several brands and traders are investing in AR to allow a unique online shopping experience. For 2025, we can expect augmented reality as one of the most interesting AI marketing tools to enhance client experience. 

By reshaping the way customers interact with products they will purchase, modern augmented reality will help boost customer engagement, reducing return rates and more confident purchases. In industries like retail, makeup, and decor, AR will be able to let clients see how a certain product will look on them, or in their space virtually. 

As AR becomes more popular and accessible, it can be expected to drastically improve the future of AI in marketing, from better engagement to increasing sales. 

Virtual Assistant 

Since Humans have been updating AI to be better and stronger than before, chatbots have become more human-like. Meaning they can engage in more natural and flowing conversation quickly, and accurately. In 2025 and further, we can expect to see more brands integrating AI chatbots into their stores and websites to offer virtual assistance to their customers rapidly. 

These AI marketing tools can perform a range of actions, from regular client interactions to aiding with payment methods, and more. The rise of Large Language models, such as GPT-4, has driven the upcoming AI marketing trends by allowing seamless, flowing conversation, and upgrading customized client interaction. 

Improved Advertisement Targeting 

These days one of the most popular AI marketing trends has been improved ad targeting. Businesses reach for their ideal clients by integrating AI. By incorporating prediction analysis along with machine-level learning, AI marketing can analyze customer behavior patterns and preferences to deliver more accurate and relative content. 

This trend may reduce ROI by decreasing the money spent on ads reaching un-targeted audiences while simultaneously optimizing engagement with the right audience. 

AI in Email Marketing

AI marketing is changing email marketing by helping businesses create more customized, targeted marketing campaigns. AI can detect audiences, personalize content, and process email sequences based on user behavior, enhancing the relatability of each communication.

By analyzing past customer preferences, AI ensures that the right email is delivered timely, boosting engagement. AI-driven email marketing will continue to be an essential strategy for reaching customers more efficiently. 

Conclusion

AI marketing influence on business is marvelous, and the future of AI in marketing can kickstart its potential to transform the industry. From customized content to detailed predictive analytics, AI has empowered traders to inspire and engage customers more effortlessly.

As businesses embrace and utilize these advancements, they will gain success in the digital world. But this does not mean that AI will advance in all fields and everything will become dependent on AI. PPC, content creation, SEO, and website development solutions are still vital to integrate for a successful online brand presence and awareness. 

At Creative’s Genie, we utilize the finest technical solutions, our experts provide you their top-notch services at discounted rates. Contact us now and get success driven to you and your online store!

[jcmarchi]

How Combining RAG with Streaming Databases Can Transform Real-Time Data Interaction

New Post has been published on https://thedigitalinsider.com/how-combining-rag-with-streaming-databases-can-transform-real-time-data-interaction/

How Combining RAG with Streaming Databases Can Transform Real-Time Data Interaction

While large language models (LLMs) like GPT-3 and Llama are impressive in their capabilities, they often need more information and more access to domain-specific data. Retrieval-augmented generation (RAG) solves these challenges by combining LLMs with information retrieval. This integration allows for smooth interactions with real-time data using natural language, leading to its growing popularity in various industries. However, as the demand for RAG increases, its dependence on static knowledge has become a significant limitation. This article will delve into this critical bottleneck and how merging RAG with data streams could unlock new applications in various domains.

How RAGs Redefine Interaction with Knowledge

Retrieval-Augmented Generation (RAG) combines large language models (LLMs) with information retrieval techniques. The key objective is to connect a model’s built-in knowledge with the vast and ever-growing information available in external databases and documents. Unlike traditional models that depend solely on pre-existing training data, RAG enables language models to access real-time external data repositories. This capability allows for generating contextually relevant and factually current responses.

When a user asks a question, RAG efficiently scans through relevant datasets or databases, retrieves the most pertinent information, and crafts a response based on the latest data. This dynamic functionality makes RAG more agile and accurate than models like GPT-3 or BERT, which rely on knowledge acquired during training that can quickly become outdated.

The ability to interact with external knowledge through natural language has made RAGs essential tools for businesses and individuals alike, especially in fields such as customer support, legal services, and academic research, where timely and accurate information is vital.

How RAG Works

Retrieval-augmented generation (RAG) operates in two key phases: retrieval and generation. In the first phase, retrieval, the model scans a knowledge base—such as a database, web documents, or a text corpus—to find relevant information that matches the input query. This process utilizes a vector database, which stores data as dense vector representations. These vectors are mathematical embeddings that capture the semantic meaning of documents or data. When a query is received, the model compares the vector representation of the query against those in the vector database to locate the most relevant documents or snippets efficiently.

Once the relevant information is identified, the generation phase begins. The language model processes the input query alongside the retrieved documents, integrating this external context to produce a response. This two-step approach is especially beneficial for tasks that demand real-time information updates, such as answering technical questions, summarizing current events, or addressing domain-specific inquiries.

The Challenges of Static RAGs

As AI development frameworks like LangChain and LlamaIndex simplify the creation of RAG systems, their industrial applications are rising. However, the increasing demand for RAGs has highlighted some limitations of traditional static models. These challenges mainly stem from the reliance on static data sources such as documents, PDFs, and fixed datasets. While static RAGs handle these types of information effectively, they often need help with dynamic or frequently changing data.

One significant limitation of static RAGs is their dependence on vector databases, which require complete re-indexing whenever updates occur. This process can significantly reduce efficiency, particularly when interacting with real-time or constantly evolving data. Although vector databases are adept at retrieving unstructured data through approximate search algorithms, they lack the ability to deal with SQL-based relational databases, which require querying structured, tabular data. This limitation presents a considerable challenge in sectors like finance and healthcare, where proprietary data is often developed through complex, structured pipelines over many years. Furthermore, the reliance on static data means that in fast-paced environments, the responses generated by static RAGs can quickly become outdated or irrelevant.

The Streaming Databases and RAGs

While traditional RAG systems rely on static databases, industries like finance, healthcare, and live news increasingly turn to stream databases for real-time data management. Unlike static databases, streaming databases continuously ingest and process information, ensuring updates are available instantly. This immediacy is crucial in fields where accuracy and timeliness matter, such as tracking stock market changes, monitoring patient health, or reporting breaking news. The event-driven nature of streaming databases allows fresh data to be accessed without the delays or inefficiencies of re-indexing, which is common in static systems.

However, the current ways of interacting with streaming databases still rely heavily on traditional querying methods, which can struggle to keep pace with the dynamic nature of real-time data. Manually querying streams or developing custom pipelines can be cumbersome, especially when vast data must be analyzed quickly. The lack of intelligent systems that can understand and generate insights from this continuous data flow highlights the need for innovation in real-time data interaction.

This situation creates an opportunity for a new era of AI-powered interaction, where RAG models seamlessly integrate with streaming databases. By combining RAG’s ability to generate responses with real-time knowledge, AI systems can retrieve the latest data and present it in a relevant and actionable way. Merging RAG with streaming databases could redefine how we handle dynamic information, offering businesses and individuals a more flexible, accurate, and efficient way to engage with ever-changing data. Imagine financial giants like Bloomberg using chatbots to perform real-time statistical analysis based on fresh market insights.

Use Cases

The integration of RAGs with data streams has the potential to transform various industries. Some of the notable use cases are:

Real-Time Financial Advisory Platforms: In the finance sector, integrating RAG and streaming databases can enable real-time advisory systems that offer immediate, data-driven insights into stock market movements, currency fluctuations, or investment opportunities. Investors could query these systems in natural language to receive up-to-the-minute analyses, helping them make informed decisions in rapidly changing environments.

Dynamic Healthcare Monitoring and Assistance: In healthcare, where real-time data is critical, the integration of RAG and streaming databases could redefine patient monitoring and diagnostics. Streaming databases would ingest patient data from wearables, sensors, or hospital records in real time. At the same time, RAG systems could generate personalized medical recommendations or alerts based on the most current information. For example, a doctor could ask an AI system for a patient’s latest vitals and receive real-time suggestions on possible interventions, considering historical records and immediate changes in the patient’s condition.

Live News Summarization and Analysis: News organizations often process vast amounts of data in real time. By combining RAG with streaming databases, journalists or readers could instantly access concise, real-time insights about news events, enhanced with the latest updates as they unfold. Such a system could quickly relate older information with live news feeds to generate context-aware narratives or insights about ongoing global events, offering timely, comprehensive coverage of dynamic situations like elections, natural disasters, or stock market crashes.

Live Sports Analytics: Sports analytics platforms can benefit from the convergence of RAG and streaming databases by offering real-time insights into ongoing games or tournaments. For example, a coach or analyst could query an AI system about a player’s performance during a live match, and the system would generate a report using historical data and real-time game statistics. This could enable sports teams to make informed decisions during games, such as adjusting strategies based on live data about player fatigue, opponent tactics, or game conditions.

The Bottom Line

While traditional RAG systems rely on static knowledge bases, their integration with streaming databases empowers businesses across various industries to harness the immediacy and accuracy of live data. From real-time financial advisories to dynamic healthcare monitoring and instant news analysis, this fusion enables more responsive, intelligent, and context-aware decision-making. The potential of RAG-powered systems to transform these sectors highlights the need for ongoing development and deployment to enable more agile and insightful data interactions.

[juealhossain]

Digital Review Fortune: Build a Review Site & Boost Earnings Fast

Are you looking to launch a review website quickly and start promoting digital products? Look no further than Digital Review Fortune. This DFY (Done-For-You) digital product review system makes it incredibly easy to set up and maintain a review site. Let's dive into what Digital Review Fortune offers and how it works.

What Is Digital Review Fortune?

Digital Review Fortune is a DFY digital product review system. It allows you to launch your review site in minutes and start promoting digital products instantly. With its user-friendly features, you can create a professional review site without much effort.

How Does It Work?

Digital Review Fortune operates in three simple steps:

Write a Review with the Custom GPT: Effortlessly generate detailed reviews by feeding the GPT tool some basic information about the product.

Copy and Paste the Review to Your Website: Once your review is ready, simply copy it and paste it into your review site’s editor.

Add Images and Publish the Review: Enhance your post by adding product images or demo videos, then hit publish to make your review live!

Features of Digital Review Fortune

Digital Review Fortune comes packed with features that make it a must-have for anyone looking to run a review site efficiently. Here are some of the key features:

Beautiful Home Page Design: A professional, clean design that positions you as an authority from day one.

Captivating Review Page Design: Engaging designs that keep your visitors hooked.

Instant Reviews with Custom GPT Tool: Generate full reviews based on basic product information in minutes.

Product Filter on Homepage: Make it easy for your visitors to find exactly what they’re looking for.

Explore Products by Categories: Organize and display products based on categories for easy navigation.

Explore Products by Vendors: Display products from specific vendors for better user experience.

Browse Products by Highlights: Showcase product highlights to attract more attention.

Bonus Vault Lists All Affiliate Bonuses: Store and manage your bonuses efficiently.

Select and Add Bonuses on Reviews: Add bonuses to any review with just a click.

Display Products of the Day: Highlight featured products for maximum visibility.

Opt-in Forms to Collect Emails: Grow your email list with built-in opt-in forms.

Built-in Bonus Claim Page: Manage bonus claims directly from your site.

Built-in Blog with DFY Blog Posts: Keep your site updated with done-for-you blog posts.

Ready-to-Use Legal Pages: Instantly ready-to-use About, Contact, FAQs, Blog, Disclaimer, Affiliate Disclosure, ToS, and Privacy Policy pages.

Built-in Product Rating System: Rate products to provide valuable insights to your visitors.

What You Get with Digital Review Fortune

Here’s what you get when you choose Digital Review Fortune:

Fully Done-For-You Review Website: A professional, clean design that positions you as an authority from day one.

Exclusive GPT Review Writing Tool: Use AI to generate full reviews based on basic product information—just copy and paste!

15+ Done-For-You Product Reviews: Start promoting top digital products right away, without writing a single word.

Product Featured Image Canva Templates: Get consistent, eye-catching visuals for your reviews, no matter what graphics the vendor provides.

Powerful Product Search & Filter: Make it easy for your visitors to find exactly what they’re looking for.

Easy-to-Manage Bonus Vault: Store and manage your bonuses, then add them to any review in just a click.

Done-for-You Pages: Instantly ready-to-use About, Contact, FAQs, Blog, Disclaimer, Affiliate Disclosure, ToS, and Privacy Policy pages.

Special Launch Price

The best part? You can grab all of this at a special launch price for just $27. Plus, use the coupon code DRFEARLYBIRD to get an additional $2 off!

Benefits of Digital Review Fortune

Digital Review Fortune offers numerous benefits:

Launch a fully-functional digital product review website in just minutes.

Generate reviews using our exclusive GPT tool from basic product details. Only a free ChatGPT account is needed.

Publish reviews in no time with pre-formatted text, perfectly structured by GPT for your site.

Easily build a comprehensive bonus vault and add any bonus to your reviews with just a click.

Create a stunning, professional-looking review site that sets you apart from the affiliate crowd.

Showcase ‘Deals of the Day’ on the homepage as featured items for maximum visibility.

Organize and display products by vendors, categories, and product highlights.

Homepage search and filter options allowing visitors to find the perfect products and reviews.

Save thousands on web design and countless hours on review writing.

Promote products like a top-tier affiliate marketer.

DFY blog posts, sub-pages, and essential legal pages.

Powered by WordPress with ready-to-use themes and plugins, newbie-friendly and designed for ease of use.

Iron-clad 30-day money-back guarantee for your complete peace of mind.

Why Is a Review Platform a Game-Changer?

1. Instant Trust

A good review platform shows you know your stuff. It helps people trust your advice. When you have clear reviews, people feel safe to follow your tips.

2. Easy Promotion Place

Your review platform helps you show off products. With good reviews and bonuses, your site can help sell products. This makes it easy for visitors to buy what you recommend.

3. Many Business Chances

A review platform gives you many ways to earn money. You can do affiliate marketing or sell websites. Digital Review Fortune helps you grow your business easily.

Pros:

Ready-Made Review Website: You get a full website right away.

Easy Review Tool: The GPT tool helps you write reviews fast.

Many Product Reviews: Start promoting with over 15 ready reviews.

Simple Product Search: Find products easily with search filters.

Bonus Vault: Store bonuses and offer them with one click.

Saves Time: The platform helps you work faster.

Nice Website Design: The site looks good and professional.

Pre-Made Legal Pages: Legal pages are ready to use.

Customize Your Site: Change the design and add your stuff.

Low Cost: Start for only $27 with extra savings available.

Easy to Use: No tech skills needed, with guides to help.

Grow Your Business: Create and sell review sites to others.

Money-Back Guarantee: Try it for 30 days without risk.

Cons:

Needs Hosting and Domain: You must pay for these to run your site.

WordPress Only: The platform only works with WordPress.

Not for Physical Products: It’s best for digital items only.

Extra Costs: Full features cost more money.

Free ChatGPT Account Needed: You must sign up for ChatGPT.

Content Overlap: Many may use the same reviews, which can be a problem.

Too Basic for Experts: Advanced users may want more features.

Focus on Specific Marketplaces: It’s mainly for certain platforms.

Email Features Need Work: The email tools are very basic.

Learning to Customize: Some parts may be hard to learn.

Funnel Information: 

1. Front-End (FE) - Digital Review Fortune 

You get a ready-made website for product reviews.

There are over 15 product reviews already written.

A tool helps you write new reviews easily.

You can change the website design to fit your style.

Search for products easily with filters.

Manage bonuses to help sell products better.

Legal pages are included, like Privacy Policy.

Training videos are there to help you.

It's great for new and average affiliate marketers. You can promote products from places like WarriorPlus and ClickBank.

2. OTO 1 - Digital Review Fortune PRO 

Get more ways to customize your website.

More design styles to make your site unique.

Extra product reviews to add to your site.

You can sell review sites to clients.

Advanced tools to customize your site with ease.

This is perfect if you want to create websites for others.

3. OTO 2 - Done-For-You Review Package 

Get 10 ready-to-use product reviews.

Content is made to help you earn money.

New reviews are added to keep your site fresh.

Each review has bonuses to help sell better.

This saves time and keeps your site updated.

4. OTO 3 - Digital Review Fortune Traffic Edition 

Learn how to get more visitors to your site.

Use social media to promote your reviews.

Use advanced SEO to help people find your site.

Get templates to help you bring in traffic.

This is great if you want more visitors and to improve your sales.

5. OTO 4 - Digital Review Fortune Agency License 

Sell Digital Review Fortune as a service to clients.

Create and sell many review websites.

Use tools to build and manage review sites.

Rebrand the product and sell it as your own.

This is good for freelancers or agencies.

6. OTO 5 - Digital Review Fortune Reseller License 

Sell Digital Review Fortune as your own product.

Keep all the money you make from sales.

Get materials to help you sell.

Resell using your own links.

Who needs It?

The Digital Review Fortune system helps many people online. Here are the groups that can use it:

Affiliate MarketersThey need a ready site to show products from ClickBank and others. This system helps them make review sites fast. They can earn money by promoting products easily. It saves time with ready reviews and bonus offers.

Beginner Online MarketersThey want an easy way to start making money online. New marketers find it hard to make sites and write reviews. This system gives them simple tools to start right away.

Freelancers or AgenciesThey need a solution to create review sites for clients. They can sell ready sites using the Agency License. This helps them earn money while helping their clients.

Intermediate to Advanced Affiliate MarketersThey need a site that helps them grow their income. These users may know some marketing but want more tools. The PRO version helps them improve their sites and earn more.

Entrepreneurs Looking for a Side IncomeThey want a simple way to earn extra money. Many want to make money without spending too much time. This system lets them set it up and earn passively.

Those Looking for Passive Income OpportunitiesThey need a simple way to earn money without much work. This system has ready content and tools to help them. It helps them earn money with less effort.

SEO Enthusiasts and Content CreatorsThey want to make content that ranks high on search engines. With SEO tools, they can improve their site’s ranking. This helps them get more visitors and earn money.

ResellersThey need a product to sell for good profits. With the Reseller License, they can sell this product as their own. They keep all the profits without making anything new.

Frequently Asked Questions

What Is Digital Review Fortune?

Digital Review Fortune is a DFY review system for digital products.

How Does Digital Review Fortune Work?

Generate reviews using GPT, copy to your site, add images, and publish.

What Features Does Digital Review Fortune Include?

It includes a beautiful home page, custom GPT tool, product filters, bonus vault, and built-in blog.

How Can I Generate Reviews Quickly?

Use the custom GPT tool to generate detailed reviews quickly.

Can I Customize My Review Site?

Yes, you can add images, videos, and customize the design.

What Are The Benefits Of Using Digital Review Fortune?

Launch a professional review site, generate reviews fast, and organize products easily.

Is There A Bonus Vault Feature?

Yes, manage and add bonuses to reviews easily with the built-in bonus vault.

How Much Does Digital Review Fortune Cost?

It costs $27, with an additional $2 off using the coupon code DRFEARLYBIRD.

Are There Pre-written Product Reviews?

Yes, it includes 15+ done-for-you product reviews.

Do I Need Technical Skills To Use This?

No, it's designed to be user-friendly and requires no technical skills.

Conclusion

Digital Review Fortune is an excellent tool for anyone looking to quickly launch a review site and promote digital products. With its easy-to-use features and professional design, you can start earning affiliate commissions in no time. Don’t miss out on this opportunity to elevate your affiliate marketing game. Grab your copy now at a special launch price and use the coupon code DRFEARLYBIRD for an additional $2 off!

For more details, visit Digital Review Fortune.

[sucharitadas]

How to develop AI Application

Here's a step-by-step guide to developing an AI-powered application:

1. Define the Problem and Goals

Understand the Problem: Identify the specific issue your AI app aims to solve (e.g., image recognition, language processing).

Set Objectives: Clearly define what you want the AI app to accomplish. This could be anything from enhancing user experience to automating business processes.

2. Research and Choose AI Models

Explore AI Techniques: Depending on the problem, you may need machine learning (ML), deep learning, natural language processing (NLP), or computer vision.

Select a Model Type: For example:

Supervised Learning: Predict outcomes based on labeled data (e.g., spam detection).

Unsupervised Learning: Find hidden patterns (e.g., customer segmentation).

Reinforcement Learning: Learn by interacting with an environment (e.g., self-driving cars).

3. Gather and Prepare Data

Data Collection: Collect relevant datasets from sources like public databases or user interactions. Ensure the data is of high quality and representative of the real-world problem.

Data Cleaning: Remove errors, handle missing values, and preprocess data (e.g., normalization or tokenization for text data).

Data Labeling: For supervised learning, ensure that your dataset has properly labeled examples (e.g., labeled images or annotated text).

4. Choose a Development Environment and Tools

Programming Languages: Use AI-friendly languages such as Python, R, or Julia.

Frameworks and Libraries:

TensorFlow or PyTorch for deep learning.

Scikit-learn for traditional machine learning.

Hugging Face for NLP models.

Cloud Platforms: Leverage platforms like Google AI, AWS, or Microsoft Azure to access pre-built models and services.

5. Build and Train AI Models

Model Selection: Choose an appropriate AI model (e.g., CNN for images, RNN for sequence data, BERT for text).

Training the Model: Use your prepared dataset to train the model. This involves feeding data into the model, adjusting weights based on errors, and improving performance.

Evaluation Metrics: Use metrics like accuracy, precision, recall, or F1-score to evaluate the model’s performance.

6. Optimize and Fine-tune Models

Hyperparameter Tuning: Adjust learning rates, batch sizes, or regularization parameters to enhance performance.

Cross-validation: Use techniques like k-fold cross-validation to avoid overfitting and ensure your model generalizes well to new data.

Use Pre-trained Models: If starting from scratch is complex, consider using pre-trained models and fine-tuning them for your specific use case (e.g., transfer learning with models like GPT or ResNet).

7. Develop the App Infrastructure

Backend Development:

Set up APIs to interact with the AI model (REST, GraphQL).

Use frameworks like Flask, Django (Python), or Node.js for backend logic.

Frontend Development:

Create the user interface (UI) using frameworks like React, Angular, or Swift/Java for mobile apps.

Ensure it allows for seamless interaction with the AI model.

8. Integrate AI Model with the Application

API Integration: Connect your AI model to your app via APIs. This will allow users to send inputs to the model and receive predictions in real-time.

Testing: Test the integration rigorously to ensure that data flows correctly between the app and the AI model, with no latency or security issues.

9. Deployment

Model Deployment: Use tools like Docker or Kubernetes to package your AI model and deploy it to cloud platforms like AWS, Azure, or Google Cloud for scaling and availability.

App Deployment: Deploy the web or mobile app on relevant platforms (e.g., Google Play Store, Apple App Store, or a web server).

Use CI/CD Pipelines: Implement continuous integration/continuous deployment (CI/CD) pipelines to automate app updates and deployments.

10. Monitor and Maintain the App

Model Monitoring: Continuously monitor the performance of the AI model in production. Watch for data drift or model degradation over time.

App Updates: Regularly update the app to add new features, improve UI/UX, or fix bugs.

User Feedback: Collect feedback from users to enhance the AI model and overall app experience.

11. Scaling and Improvements

Scale the App: Based on user demand, optimize the app for scalability and performance.

Retraining Models: Periodically retrain your AI model with new data to keep it relevant and improve its accuracy.

By following these steps, you can create a well-structured AI application that is user-friendly, reliable, and scalable.

[jagrav25]

Top SEO Trends to Watch in 2024

Search engine optimization (SEO) is a constantly evolving landscape. To stay ahead of the competition, it’s essential to keep up with the latest trends and algorithm updates that shape how websites rank on search engines like Google. As we move into 2024, a few key SEO trends are emerging that digital marketers need to watch closely. Whether you’re running a blog, an e-commerce store, or a large corporate website, understanding these trends will be crucial to maintaining visibility in search engine results pages (SERPs).

Here’s a look at the top SEO trends you should focus on in 2024 to keep your digital strategy sharp and effective.

1. AI-Driven SEO and Content Creation

Artificial Intelligence (AI) is transforming SEO in many ways, and this trend is only expected to grow in 2024. AI tools like OpenAI’s GPT models and Google’s MUM (Multitask Unified Model) are enhancing search engines’ ability to understand complex queries and provide more relevant search results.

How AI Impacts SEO:

Content Optimization: AI tools help marketers optimize their content for search engines by analyzing keywords, competitors, and user intent at a much deeper level.

Content Creation: AI can assist with content generation, from writing blog posts to generating meta descriptions, freeing up time for strategic planning.

User Experience: AI helps search engines understand user behavior more effectively, which means that websites offering the best user experience will rank higher.

What to Do:

Leverage AI-powered tools like Clearscope, SurferSEO, or ChatGPT to refine your content strategy. Use them to analyze competitors, identify content gaps, and create content optimized for both user intent and search engines.

2. Google’s Core Web Vitals and Page Experience

Core Web Vitals have been a ranking factor since 2021, and their importance continues to grow. Google evaluates websites based on three key factors—Largest Contentful Paint (LCP), First Input Delay (FID), and Cumulative Layout Shift (CLS)—to determine how user-friendly and fast-loading a page is.

Key Metrics:

LCP: Measures loading performance. It should occur within 2.5 seconds of when the page first starts loading.

FID: Measures interactivity. Pages should have an FID of less than 100 milliseconds.

CLS: Measures visual stability. Your page should maintain a CLS of less than 0.1.

What to Do:

Regularly audit your site using Google’s PageSpeed Insights or Lighthouse tools. Focus on improving loading times, reducing server response time, optimizing images, and minimizing layout shifts to boost your Core Web Vitals scores.

3. Voice Search Optimization

Voice search is becoming more common as digital assistants like Siri, Alexa, and Google Assistant continue to rise in popularity. In 2024, optimizing for voice search will be key, as people are increasingly using spoken queries, which are often longer and more conversational.

Voice Search Trends:

Natural Language Processing (NLP): Google’s algorithms are increasingly capable of understanding natural, conversational language.

Question-Based Queries: Voice searches often take the form of questions. People ask things like “What’s the best restaurant near me?” or “How do I fix a leaky faucet?”

What to Do:

Incorporate long-tail keywords and question-based content into your SEO strategy. Optimize your content to answer specific user queries using FAQ sections and conversational language. Structured data and featured snippets are particularly useful for voice search optimization.

4. E-E-A-T: Experience, Expertise, Authority, and Trustworthiness

Google has expanded the original E-A-T framework (Expertise, Authority, Trustworthiness) to include Experience. This means search engines will favor content created by individuals or entities with firsthand experience on the topic. This update emphasizes the importance of authentic, high-quality content.

How E-E-A-T Impacts SEO:

Experience: Demonstrating first-hand knowledge of a subject boosts your credibility.

Expertise: Google rewards content from recognized experts in a given field.

Authority: The overall reputation of the content creator or website matters.

Trustworthiness: Google wants to see secure websites with clear privacy policies, trust signals (e.g., reviews, testimonials), and accurate information.

What to Do:

Make sure your content is created or reviewed by experts. Highlight your credentials or partnerships with reputable sources. Build backlinks from authoritative sites, focus on gathering positive reviews, and improve on-page SEO elements like author bios.

5. Multimodal Search with Google’s MUM

Google’s MUM (Multitask Unified Model) technology is revolutionizing how search queries are processed by combining information from text, images, videos, and other sources to provide richer search results. MUM is 1,000 times more powerful than its predecessor, BERT, and is expected to play a major role in search rankings moving forward.

What This Means for SEO:

Visual and Textual Content Integration: Your website should incorporate not just text, but also images, videos, and other multimedia that enriches the user’s experience.

Multilingual Capabilities: MUM is able to process information across different languages, so creating content that can appeal to global audiences could increase your visibility in international markets.

What to Do:

Diversify your content strategy by integrating videos, images, and podcasts into your website. Optimize all multimedia with appropriate titles, descriptions, and alt text for better search indexing.

[thenextaitool]

OpenAI DevDay SF

Today at DevDay SF, OpenAI is launching a bunch of new capabilities to the platform.

Realtime API

The new Realtime API, now in public beta, allows paid developers to create low-latency, speech-to-speech experiences in apps, similar to ChatGPT’s Advanced Voice Mode. It supports real-time streaming of audio inputs and outputs, offering more natural and responsive conversations. Alongside this, an update to the Chat Completions API introduces audio input and output, supporting multimodal interactions with text or audio responses. These updates simplify the process for developers by consolidating speech recognition, text processing, and speech synthesis into a single API call, enhancing use cases like customer support and language learning.

Prompt Caching

Prompt Caching, introduced today, allows developers to reuse recently seen input tokens across multiple API calls, reducing both costs and latency. This feature provides a 50% discount and faster prompt processing times. Prompt Caching is automatically applied to the latest versions of GPT-4o, GPT-4o mini, o1-preview, o1-mini, and their fine-tuned counterparts.

Model Distillation

OpenAI is introducing a new Model Distillation offering, providing developers with an integrated workflow to manage the entire distillation pipeline directly within the platform. Model distillation fine-tunes smaller, cost-efficient models using outputs from more capable models, improving performance at a lower cost. This suite simplifies the previously complex, multi-step process with three key features: Stored Completions, which captures input-output pairs to build datasets for fine-tuning; Evals, a tool for custom performance evaluations; and seamless integration with OpenAI’s fine-tuning services. This offering reduces manual effort and streamlines model optimization.

Vision Fine-Tuning

OpenAI has introduced vision fine-tuning on GPT-4o, allowing developers to fine-tune the model using images in addition to text. This enhances the model’s image understanding capabilities, enabling applications such as improved visual search, better object detection for autonomous systems, and more accurate medical image analysis. While many developers have used text-only fine-tuning to improve task-specific performance, the addition of image fine-tuning addresses the limitations of text-based models for more complex, visual tasks.

For more news like this: thenextaitool.com/news

[pacificleo]

privacy policy template

At [Your Company Name], we are committed to protecting your privacy and ensuring the security of your personal information. This Privacy Policy outlines how we collect, use, disclose, and safeguard your information when you interact with our custom GPT model. By using our services, you agree to the collection and use of information in accordance with this policy.

1. Information We Collect

When you interact with our custom GPT model, we may collect the following types of information:

a) Personal Information:

User Inputs: Any text, questions, or prompts you provide to the custom GPT model. This may include personal information if shared by you.

Account Information: If applicable, when you create an account or log in, we may collect your name, email address, and other contact details.

b) Usage Data:

Log Data: We automatically collect information about your usage of the custom GPT model, such as the IP address, browser type, session duration, and interactions with the model.

Cookies: We may use cookies to collect information about your device and interactions with our website or app.

2. How We Use Your Information

We use the information we collect for the following purposes:

To Provide and Improve the Service: We use user inputs to generate responses and improve the performance of the custom GPT model.

Communication: We may use your contact information to respond to inquiries, provide customer support, or send important updates about the service.

Research and Development: Aggregated, non-identifiable data may be used to enhance the performance and capabilities of the GPT model.

Compliance: We may process personal information to comply with legal obligations.

3. Data Retention

We retain personal data only for as long as necessary to fulfill the purposes outlined in this Privacy Policy or as required by law. User inputs may be anonymized and stored for research or model improvement purposes.

4. How We Share Your Information

We do not sell or rent your personal information to third parties. However, we may share your information in the following circumstances:

Service Providers: We may share information with third-party vendors, consultants, and service providers who work on our behalf and need access to your information to carry out their services.

Legal Requirements: We may disclose your information if required by law or to protect the rights, property, or safety of our company or others.

Business Transfers: In the event of a merger, acquisition, or sale of assets, your information may be transferred as part of that transaction.

5. Security

We take reasonable measures to protect the personal information you provide to us from unauthorized access, disclosure, alteration, or destruction. However, no method of transmission over the Internet or electronic storage is 100% secure, and we cannot guarantee absolute security.

6. Your Rights

Depending on your location and applicable laws, you may have the following rights regarding your personal information:

Access: You have the right to request access to the personal information we hold about you.

Correction: You can request that we correct any inaccurate or incomplete information.

Deletion: You may request the deletion of your personal information.

Data Portability: You have the right to request a copy of your personal data in a structured, commonly used format.

To exercise any of these rights, please contact us at [Contact Information].

7. Children's Privacy

Our service is not intended for use by children under the age of 13. We do not knowingly collect personal information from children under 13. If we become aware that we have collected such information, we will take steps to delete it.

8. Changes to this Privacy Policy

We may update this Privacy Policy from time to time to reflect changes in our practices or legal requirements. Any updates will be posted on this page, and the "Last Updated" date at the top will be revised.

9. Contact Us

If you have any questions or concerns about this Privacy Policy or our data practices, please contact us at:

[Your Company Name] Email: [Your Contact Email] Phone: [Your Contact Number] Address: [Your Physical Address, if applicable]

[maiosx]

This is exactly why Elon was kicked off rally 5.5

he is really not smart at all. A single baby wogue video on LLM used in the file explorer of gnome has more usable code than his entire ChatGPT project did but bc ppl don’t understand it, they flock to elons side, and regardless, Apple GPT wouldn’t be used to make instructables for ppl to cheat on apps or crypto projects, it would be used for real world interactions instead, like the real gnome project, humanity - Apple GPT is Fuck your trolly billionaire wannabe status LLM set kinda tech bc they have the power to actually implement it system wide instead of just as a single app that can’t interface with anything. This is the problem with normie billionaires, they don’t understand how to make things that are actually useable day to day. Too many of them think they can just get rich selling some crypto and super fast thing, but in the end, the people that take their time to work on their ideas actually end up making better things, and he purposefully took off tweeted from an iPhone or android just to piss off ppl that don’t wanna work at Tesla bc the pay is low and FSD upgrades are BS. Since when has Apple charged for an iOS update.. never. All their OSes are free to use if you can attain the hardware. It is up to users to decide whether they want to brew their own software experience or use something that people that understand bits down to the networking protocol bytes make. I don’t support any of Elon’s companies or projects and neither should anybody. They are all pre-made things others worked on that he bought and imposed restrictions and upgrade services on bc instead of innovating further, for example like creating a bunch of Tesla hotels with solar roofs for ppl to visit or Tesla locations to airbnb at, using his boring tunnels, with his own “teslabnb”, he wouldn’t need to charge for FSD, and if those teslabnbs had starlink Wi-Fi that ppl paid to use, then twitter wouldn’t need 8 dollars a month and Tesla employees wouldn’t have low wages. His ego is literally trolling users. People are not so smart to see it but if they did, they would say Elon is full of shit bc all the examples I just gave took me two seconds to come up with and billionaires practically live at hotels, so he probably already thought of it but would never do that just to keep that carrot on a stick metaphor in our minds and so he can keep pretending he is anti-1984, keeps feeding us that lefty righty political bs but never really implements the solutions above to stop it. It is billionaires that created 1984 and they know a way out, but they are full of shit. I can’t even long post this on Twitter bc he wants 8 dollars to do so, and this dude has been riding on apple’s platform success since twitter launched on iPhone and it should just be deleted off the App Store for not even using usps logic.

[govindhtech]

Boost the development of AI apps with Cloud Modernization

Cloud Modernization

A new era of intelligent applications that can comprehend natural language, produce material that is human-like, and enhance human abilities has begun with the development of generative AI. But as businesses from all sectors start to see how AI may completely transform their operations, they frequently forget to update their on-premises application architecture, which is an essential first step.

Cloud migration

Cloud migration is significantly more advantageous than on-premises options if your company wants to use AI to improve customer experiences and spur growth. Numerous early adopters, including TomTom and H&R Block, have emphasized that their decision to start updating their app architecture on Azure was what prepared them for success in the AI era.

Further information to connect the dots was provided by a commissioned study by IDC titled “Exploring the Benefits of Cloud Migration and Cloud Modernization for the Development of Intelligent Applications,” which was based on interviews with 900 IT leaders globally regarding their experiences moving apps to the cloud. They’ll go over a few of the key points in this article.

Modernise or lag behind: The necessity of cloud migration driven by AI

Let’s say what is obvious: Artificial Intelligence is a potent technology that can write code, produce content, and even develop whole apps. The swift progress in generative AI technologies, such OpenAI’s GPT-4 has revolutionized the way businesses function and engage with their clientele.

However, generative AI models such as those that drive ChatGPT or image-generating software are voracious consumers of data. To achieve their disruptive potential, they need access to enormous datasets, flexible scaling, and immense computing resources. The computation and data needs of contemporary AI workloads are simply too much for on-premises legacy systems and compartmentalized data stores to handle.

Cloud Modernization systems, which are entirely managed by the provider, offer the reliable infrastructure and storage options required to handle AI workloads. Because of its nearly infinite scalability, apps can adapt to changing demand and continue to operate at a high level.

The main finding of the IDC survey was that businesses were mostly driven to move their applications to the cloud by a variety of benefits, such as enhanced security and privacy of data, easier integration of cloud-based services, and lower costs. Furthermore, companies can swiftly test, refine, and implement AI models because to the cloud’s intrinsic agility, which spurs innovation.

With its most recent version, the.NET framework is ready to use AI in cloud settings. Developers can use libraries like OpenAI, Qdrant, and Milvus as well as tools like the Semantic Kernel to include AI capabilities into their apps. Applications may be delivered to the cloud with excellent performance and scalability thanks to the integration with.

NET Aspire. H&R Block’s AI Tax Assistant, for instance, shows how companies may build scalable, AI-driven solutions to improve user experiences and operational efficiency. It was developed using.NET and Azure OpenAI. You may expedite development and boost the adoption of AI in all areas of your company operations by integrating. NET into your cloud migration plan.

Utilising cloud-optimized old on-premises programmes through migration and restructuring allows for the seamless scaling of computation, enormous data repositories, and AI services. This can help your business fully incorporate generative AI into all aspects of its data pipelines and intelligent systems, in addition to allowing it to develop generative AI apps.

Reach your AI goals faster in the cloud

The ambition of an organisation to use generative AI and the realisation of its full value through cloud migration are strongly correlated, according to a recent IDC study. Let’s dissect a few important factors:

Data accessibility: Consolidating and accessing data from several sources is made easier by cloud environments, giving AI models the knowledge they require for training and improvement.

Computational power: Elastic computing resources in the cloud may be flexibly distributed to fulfil complicated AI algorithm needs, resulting in optimal performance and cost effectiveness.

Collaboration: Data scientists, developers, and business stakeholders may work together more easily thanks to cloud-based tools, which speeds up the creation and application of AI.

Cloud migration speeds up innovation overall in addition to enabling generative AI. Cloud platforms offer an abundance of ready-to-use services, such as serverless computing, machine learning, and the Internet of Things, that enable businesses to quickly develop and integrate new intelligent features into their apps.

Adopt cloud-based AI to beat the competition

Gaining a competitive edge is the driving force behind the urgent need to migrate and modernise applications it’s not simply about keeping up with the times. Companies who use AI and the cloud are better positioned to:

Draw in elite talent Companies with state-of-the-art tech stacks attract the best data scientists and developers.

Adjust to shifting circumstances: Because of the cloud’s elasticity, organisations may quickly adapt to changing client wants or market conditions.

Accelerate the increase of revenue: Applications driven by AI have the potential to provide new revenue streams and improve consumer satisfaction.

Embrace AI-powered creativity by updating your cloud

Cloud migration needs to be more than just moving and lifting apps if it is to stay competitive. The key to unlocking new levels of agility, scalability, and innovation in applications is Cloud Modernization through rearchitecting and optimizing them for the cloud. Your company can: by updating to cloud-native architectures, your apps can:

Boost performance: Incorporate intelligent automation, chatbots, and personalised recommendations all enabled by AI into your current applications.

Boost output: To maximise the scalability, responsiveness, and speed of your applications, take advantage of cloud-native technology.

Cut expenses: By only paying for the resources you use, you can do away with the expensive on-premises infrastructure.

According to the IDC poll, most respondents decided to move their apps to the Cloud Modernization because it allowed them to develop innovative applications and quickly realize a variety of business benefits.

Boost the development of your intelligent apps with a cloud-powered AI

In the age of generative AI, moving and updating apps to the cloud is not a choice, but a requirement. Businesses that jump on this change quickly will be in a good position to take advantage of intelligent apps’ full potential, which will spur innovation, operational effectiveness, and consumer engagement.

The combination of generative AI and cloud computing is giving organizations previously unheard-of options to rethink their approaches and achieve steady growth in a cutthroat market.

Businesses may make well-informed decisions on their cloud migration and Cloud Modernization journeys by appreciating the benefits and measuring the urgency, which will help them stay at the forefront of technical advancement and commercial relevance.

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