#4v new model

[venkateshwheelsbingo]

The maker of TVS is coming out with the "Blaze of Black" version for the models RTR 160 and RTR 160 4V which are the most popular motorcycles. These latest versions are getting priced at Rs. 1.20 lakh in the ex-showroom. The second edition in the line, however, has a chic blacked-out design which is not only eye-catching but also uniquely stylish. The sporty appearance of the bike is accentuated by a shiny black finish and a black TVS Apache stallion logo on the tank and the exhaust system too is fully black. However, the only difference is that the bike will come in a new paint scheme. All mechanics aspects are unchanged.

[mvishnukumar]

Difference between Big Data and Machine Learning

Big Data: 

Big data refers to extremely large datasets that are often complex, unstructured, and difficult to process using traditional data management tools. The primary goal of big data is to collect, store, and analyze data to extract useful information. It deals with techniques for handling, processing, and analyzing massive datasets efficiently using technologies like Hadoop, Apache Spark, and distributed computing. The focus is on volume, variety, velocity, and veracity (the 4Vs of big data).

Machine Learning: 

Machine learning (ML) is a subset of artificial intelligence that focuses on creating algorithms that allow computers to learn from data. The goal is to identify patterns in the data and use them to make predictions or decisions without explicit programming for each task. It requires various mathematical, statistical, and algorithmic techniques. ML models rely on data for training, and once trained, they can make predictions on new data. Popular ML libraries include TensorFlow, PyTorch, and Scikit-learn.

Programming Skills: 

While both require programming, machine learning usually demands a deeper understanding of algorithms, mathematical concepts, and coding for tasks like model building, training, and optimization. Big data typically requires knowledge of data pipelines, data storage, and analytics, often relying on tools that automate much of the process, meaning it might require less hands-on coding but a stronger understanding of the data architecture.

[innonurse]

NIH research highlights the risks and benefits of incorporating AI into medical decision-making

- By InnoNurse Staff -

Researchers at the National Institutes of Health (NIH) found that an AI model accurately answered medical quiz questions designed to test health professionals' diagnostic abilities using clinical images and text summaries. However, the AI made mistakes in describing images and explaining its decision-making.

The study, published in npj Digital Medicine, highlights AI's potential in clinical settings but emphasizes that human experience remains crucial for accurate diagnosis. 

The research involved comparing the AI model's and physicians' answers to questions from the New England Journal of Medicine's Image Challenge. The AI often selected the correct diagnosis more frequently in closed-book settings, but physicians outperformed the AI when using external resources, particularly on more difficult questions. 

The study suggests further evaluation of multi-modal AI technology is needed before clinical integration, noting its potential to augment clinical decision-making with data-driven insights. 

The study used GPT-4V and was a collaborative effort across several institutions.

Read more at NIH

///

Other recent news and insights

A new video-based test for Parkinson's employs AI to monitor the disease's progression (University of Florida)

India: Acko acquires health tech startup OneCare (The Economic Times)

[ryjuegos]

The Future of Artificial Intelligence in Technology: Trends and Predictions for 2024

Welcome to an exciting look at the future of artificial intelligence (AI) in technology. As we head towards 2024, AI is changing fast. It's bringing new ways to live, work, and interact with the world. The past year saw a big jump in generative AI, catching everyone's attention and starting to blend into business.Now, 2024 looks like a key year. Researchers and companies are working hard to make this new tech a part of our everyday lives. The growth of generative AI shows how computers are changing, moving from big, complex models to smaller, smarter ones.Open-source projects are leading the way in innovation. They're making AI more accessible to everyone, not just big companies. In this article, you'll learn about the main trends and predictions for AI's future. You'll see how AI will become more open, how it will work with different kinds of data, and how it will make experiences more personal.Key Takeaways - Generative AI has seen significant growth in public awareness and business integration since 2022. - Open-source large language models are challenging proprietary solutions, driving innovation and democratization. - Smaller, more efficient AI models are becoming popular, enabling edge computing and improved explainability. - Multimodal AI models that can process text, images, and video are emerging, unlocking new applications. - AI regulation and governance are gaining traction to ensure responsible and ethical deployment.

Democratization of AI: Smaller Models and Open-Source Advancements

The democratization of artificial intelligence (AI) is changing the tech world. Smaller AI models are getting more powerful and easy to use. This makes AI available to more people. Open-source projects are also pushing innovation forward, making AI more accessible to everyone.Empowering AI Adoption with Smaller ModelsGartner says democratized AI will be a big change in the next decade. It's all about making AI tools and skills available to everyone. Smaller AI models like Google Cloud AutoML and IBM's Watson are making AI useful for all kinds of businesses. This makes AI easier for people who aren't experts to use. - AI tools like Tableau and Power BI make it easy to understand complex data. They help users get insights fast without needing special skills. - Tools such as Miro and Mural use AI to help with brainstorming and showing ideas. This shows how AI can help teams work together better. - AI tools like Copy.ai and Jasper help with making content by creating text from prompts. This makes making content faster. AI is making things more efficient, customer-focused, and profitable in many industries. It's letting more people use this powerful technology.Open-Source Initiatives Driving InnovationOpen-source projects are also key in making AI better and more accessible. Projects like TensorFlow, PyTorch, and Scikit-learn let people work together on AI. This makes AI development more open and inclusive."The democratization of AI is speeding up progress, sparking new ideas, and opening doors for big changes in society."Platforms like GitHub help developers work together on AI projects. These efforts are narrowing the gap with commercial AI, making advanced AI tools available to more people.

The trend of democratizing AI is giving more people the chance to use this technology. With smaller AI models and more open-source projects, the future of AI looks bright. It will bring more innovation and make the tech world more open to everyone.

Multimodal AI: The Next Frontier

The future of artificial intelligence (AI) is set to make a huge leap with multimodal AI models. These advanced systems can handle and analyze different types of data like text, images, and video. This opens up new possibilities for more natural and flexible uses.Models like OpenAI's GPT-4V and Google's Gemini are at the forefront of this change. They can switch easily between tasks that involve understanding language and tasks that involve seeing images. This lets them understand the world in a deeper way.Unlocking Diverse InsightsMultimodal AI models work best when they use different kinds of data together. This helps them find insights that would be hard or impossible to get from just one type of data. For example, in healthcare, these models can look at medical images, patient stories, and genetic info to spot diseases early and treat them better. Autonomous cars also use this kind of AI to make sense of camera, radar, and sensor data for safer driving.But the advantages of multimodal AI aren't just for these specific areas. In customer service, advanced chatbots can understand text, voice, and facial expressions for better conversations. In entertainment, it makes games and movie recommendations more engaging by combining what we see and hear.As multimodal AI keeps getting better, the future looks very exciting. By using a mix of data types, these models will open up new ways to innovate. They will change industries and how we use technology in our daily lives."Multimodal AI represents the next frontier in artificial intelligence, enabling us to unlock unprecedented levels of understanding and create applications that are more intuitive, versatile, and impactful than ever before."

Personalized AI: Tailored Experiences and Insights

Personalized AI and tailored AI-powered experiences are changing how we use technology. Companies use AI-powered experiences to make interactions more personal and engaging. They focus on what each user likes and needs.Big names like Google, Apple, and Samsung lead this change. They focus on AI personal assistants that work well with users' data. This makes customer service more insightful and personal than ever. - Fast-growing companies gain 40% more revenue from personalization than slower-growing companies. - 71% of consumers expect personalized experiences from companies. - 76% of consumers get frustrated when they don't get the personal touch they expect. AI lets businesses analyze lots of data and predict what customers might want next. This means they can send targeted marketing messages. Personalized AI grabs customers' attention and builds stronger bonds with them."AI personalization helps businesses present the right products or services, increasing the likelihood of conversion and revenue growth."But, using AI-powered experiences comes with challenges. Companies must keep things human and follow strict data rules. Finding the right mix of tech and personal touch is key. This way, businesses can make the most of personalized AI and give customers experiences they love.

Artificial Intelligence in Technology: Trends and Predictions

2024 is set to bring big changes and new trends in artificial intelligence (AI). The big language models will keep leading the way. But, it's important for businesses and tech fans to watch for new AI advancements.Big tech companies are facing a challenge to make money from their generative AI. This might lead to easier-to-use platforms for everyone. These platforms will let more people use powerful language models.Text-to-video is another big area in AI. Startups like Runway are making high-quality videos easily. But, they need to fix issues with reliability and bias in these AI models.AI isn't just about language and making content. It's changing how industries work and making things more efficient. AI helps businesses make better decisions and improve customer experiences with tools like personalized marketing and predictive analytics.As AI gets more popular, companies need to use it wisely and think about ethical AI. The future of AI is bright, and those who focus on responsible AI will lead the way."AI is no longer a futuristic concept; it is transforming how we live, work, and interact with technology. The trends and predictions for 2024 showcase the incredible potential of this technology to revolutionize various industries and create new opportunities for businesses and consumers alike."

Governance and Responsible AI

AI technology is becoming more common, making us focus on governance, safety, and security. Companies now see the importance of keeping AI safe and secure. This is to protect their good name. Big companies are setting clear rules for their AI use. They aim to be innovative yet responsible, avoiding mistakes and ensuring fairness.Data governance tools are key for responsible AI. They help organize and automate how data is handled. This keeps companies in line with laws and makes sure their AI is trustworthy.The Importance of AI GovernanceAI governance is a team effort in big companies. The CEO and top leaders set the rules for using AI responsibly. They see AI as a way to improve customer service, change business for the better, and make things more efficient. But, there are worries about AI being used ethically and fairly."Responsible AI is about designing, building, and deploying AI systems in a manner that empowers individuals and businesses while ensuring equitable impacts on customers and society." - World Economic ForumIt's important to have clear rules for AI use. This means making sure AI goals match business goals, checking risks, and making sure data and models are used right. Following laws and guidelines is also key.Keeping an eye on AI systems is crucial for their performance and fairness. As AI grows in fields like healthcare and finance, having good AI rules is more important than ever.

Domain-Specific AI Models in the Enterprise

Enterprises are moving towards specialized AI models. These models are more accurate and efficient, offering real value in business. This marks a new chapter in AI for companies.Companies are seeing the perks of AI models made for their specific needs. For instance, a healthcare firm uses a GPT model for precise cost predictions. A software company uses MagnifAI to improve customer analysis and upselling.Domain-specific AI models bring many benefits. They give better results, speed up progress, and solve problems cost-effectively. These models use pre-trained data from various industries to meet specific sector or use case needs.The global market for generative AI is set to hit $110.8 billion by 2030. Companies are fine-tuning these models for their unique data to beat general AI's limits. This is changing how e-commerce, product design, and quality control work."Domain-specific AI solutions like MagnifAI provide more efficiency and help generate better business decision-making insights."The future of AI in business is about using specialized models for unique challenges. By adopting domain-specific AI, companies can solve big problems faster. This leads to more ROI and a competitive edge online.

AI Regulation and Compliance

As AI technology gets better, governments and companies are working on rules for it. They worry about risks like threats to security and rogue AI. Some companies see rules as a way to grow, while others aim for responsible AI use.The European Union has made big steps with its AI Act. This could set a standard for AI rules worldwide. In the US, some states have made their own AI laws, and more might do the same. The American Data Protection and Privacy Act and a White House Executive Order also address AI rules.Companies focus on AI compliance to protect their reputation. Legal advice is key for checking if AI rules are followed. Companies using AI must make sure it's fair, transparent, and doesn't change in bad ways."Unregulated AI may lead to unfair outcomes due to the amplification of biases in data, with evolving algorithms that are difficult to explain and may change based on new data."There's no single US law for AI yet, but top AI governance companies are making their own rules. As people learn more about AI risks, the need for strong laws grows.The rules for AI are changing fast. Companies and users must keep up with AI compliance to use this powerful tech right.

The Rise of Personal AI Assistants

AI is getting more personal and tailored for each user. This means personal AI assistants will become a big deal soon. Google Gemini and Google Workspace use your data to give you personalized experiences and insights.Apple and Samsung are focusing on on-device AI for privacy and quick access. This means your personal AI could be a big part of your life. It could help with relationships, learning, and your career by giving you advice and recommendations.AI-powered virtual assistants are getting more common at home. Siri and Alexa show how well they can understand and respond to what you say. These assistants make using technology better, more engaging, and keep customers coming back.As technology gets better, expect to see AI assistants that are smarter, more flexible, and fit your needs perfectly. They will make managing your digital life easier and more efficient. Read the full article

[jhavelikes]

We are excited to introduce our largest and most capable model yet, Reka Core. It is a frontier-class multimodal language model on par with leading models in the industry today. Core was efficiently trained from scratch on thousands of GPUs over a period of a few months. Performance highlights Core is competitive with models from OpenAI, Anthropic, and Google across key industry-accepted evaluation metrics. Given its footprint and performance, on a total cost of ownership basis, Core delivers outsized value. The combination of Core’s capabilities and its deployment flexibility unlocks vast new use cases. Core is comparable to GPT-4V on MMMU, outperforms Claude-3 Opus on our multimodal human evaluation conducted by an independent third party, and surpasses Gemini Ultra on video tasks. On language tasks, Core is competitive with other frontier models on well-established benchmarks.

Reka Core: Our Frontier Class Multimodal Language Model — Reka AI

[wbtodays]

Bajaj Pulsar 500 Twinner Cafe Racer: Exploring The New Pulsar

The Pulsar 500 Twinner Cafe Racer a Trademarked Bike 2024

Bajaj Auto, a big name in India's bike world, has something exciting up its Pulsar 500 Twinner Cafe Racer. Get set for an awesome ride with the Pulsar 500 Twinner Cafe Racer! It's not a myth anymore – it's a real blend of classic cool and modern muscle. Inside, a powerful 500cc twin-cylinder engine is ready to unleash 60 horses of pure excitement. With a sleek design and no extra frills, it effortlessly cruises through the air. Low handlebars and a solo seat make you one with the bike, while the teardrop fuel tank and clipped tail keep the focus on speed.

This bike takes you back to the carefree days of wide roads, cozy leather coats, and wind in your hair. It's more than just a simple bicycle. Seizing the opportunity to embark on an incredible journey is imperative, as the Pulsar 500 Twinner Cafe Racer is not just following but also leading the road.

Bajaj Pulsar 500 Twinner Cafe Racer (Expected Specifications)

The Pulsar 500 Twinner Cafe Racer is not yet officially launched, and these are estimated specifications based on rumors and reports. FeatureSpecificationEngineTwin-cylinder, 4-valve, DOHC, liquid-cooledDisplacement499cc (estimated)Power60 bhp (estimated)Torque50 Nm (estimated)Transmission6-speed gearboxChassisPerimeter frameSuspensionTelescopic forks (front), monoshock (rear)BrakesDisc brakes (front and rear)ABSDual-channel ABS (expected)TiresTubeless tires (likely)Fuel Tank Capacity15 liters (estimated)Seat Height780mm (estimated)Weight180kg (estimated)

Double the Power Fun

For a brand known for single-cylinder bikes, Bajaj is cooking up a surprise—a twin-cylinder engine. Imagine the thrill! Could it be the answer to the cool success of Royal Enfield's twin-cylinder 650 platform? Rumor has it that Bajaj and KTM were planning a 490cc twin-cylinder engine in 2020, and they even trademarked it as Twinner.

Twinner: No Frills, Just Thrills

Bajaj's Twinner trademark is refreshingly simple. No extra tags. This hints at it blending smoothly with existing models like the Pulsar. Picture this: Bajaj Pulsar 500 Twinner, where Twinner becomes the stamp of a new riding experience.

Style and Substance by Design

A guy named Pratyush Rout is behind the cool design. He mixed Pulsar's tough look with classic touches. Think round headlights like the first Pulsar, a sporty stepped rear seat, and a tweaked fuel tank. It's like a mashup of styles from different bike worlds.

Features That Turn Heads

The Pulsar 500 Twinner borrows some cool stuff from the Dominar 400, like those round headlights that nod to motorcycle history. The instrument cluster rocks twin circular pods, adding a touch of class. Golden front forks and Nissin calipers on disc brakes make it look even more awesome. If it hits the market, it'll outshine the soon-to-be-launched 400cc single-cylinder Pulsar.

Performance in the Spotlight

Get ready for some power! The Pulsar 500 Twinner aims for around 60 bhp of power and 50Nm of torque, thanks to a wider engine. It's not just about power; it's packed with modern features like a 4V head, DOHC setup, liquid cooling, quick-shifter, throttle-by-wire, and a slipper clutch for a super fun ride. https://www.youtube.com/watch?v=ZE7yAKPcuiw&pp=ygUOVGhlIFB1bHNhciA1MDA

Wrapping it Up

Bajaj's dive into twin-cylinder engines, hinted by the Twinner trademark and the sneak peek of the Pulsar 500 Twinner, is a big move. It's a mix of cool design and powerful performance, setting the stage for an exciting chapter in Bajaj's motorcycle story.

FAQs

When can I get my hands on the Pulsar 500 Twinner?The launch date is still a secret. Keep an eye on Bajaj Auto's updates for the scoop.How does the Pulsar 500 Twinner compare to other bikes?We'll spill the beans after experts review the bike post-launch.What's the deal with the Pulsar 500 Twinner's engine?Expect a power-packed experience with modern features for an upgraded ride.Is the Pulsar 500 Twinner priced just right?No word on pricing yet, but Bajaj Auto usually keeps it competitive.Can I jazz up my Pulsar 500 Twinner?Customization details will roll out post-launch. Stay tuned for ways to personalize your ride! Read the full article

[govindhtech]

Latest Marvels : Azure AI Data & Digital Apps Advancements

Azure AI Data, AI, and Digital Apps updates:

Modernize data, build smart apps, and use AI

Generational AI models and tools have improved application and business process experiences for years, but this year was a turning point.  Within months, customers and partners integrated AI into their transformation roadmaps and launched AI-powered Digital Apps and services.

A new technology has never caused such rapid change. It shows how many organizations were AI-ready and how cloud, data, DevOps, and transformation cultures prepared them. Customers and partners can maximize AI with hundreds of Microsoft resources, models, services, and tools this year.

New models and multimodal capabilities in Azure AI

They offer the most advanced open and frontier models so developers can build confidently and unlock immediate value across their organization. 

They added Models as a Service to Azure OpenAI Service last month. Azure AI applications can use model providers’ latest open and frontier LLMs.

MaaS for Llama 2 was announced last week. The ready-to-use API and token-based billing of MaaS for Llama 2 let developers integrate with their favorite LLM tools like Prompt Flow, Semantic Kernel, and LangChain. Hosted fine-tuning lets generative AI developers use Llama 2 without GPUs, simplifying model setup and deployment. Llama 2, purchased and hosted on Azure Marketplace, lets them sell custom apps. In his blog post, John Montgomery describes this announcement and shows Azure AI Model Catalog models. 

Here are improving Azure OpenAI Service and launched multimodal AI to let businesses build

Generative AI experiences with image, text, and video:

Preview DALL·E 3: Generate images from text descriptions. The AI model DALL·E 3 excels in this regard. DALL·E 3 generates images from user descriptions.

General availability: GPT-3.5 Turbo preview at

16k token prompt:

GPT-4 Turbo: Azure OpenAI Service models now extend prompt length and improve generative AI application control and efficiency.

Visionary GPT-4 Turbo preview: GPT-4V optimises experiences by generating text output from images or videos using Azure AI Vision enhancements like video analysis.

Modifying Azure OpenAI Service models: Fine-tune Azure OpenAI Service models Babbage-002, Davinci-002, and GPT-35-Turbo. Developers and data scientists can customize Azure OpenAI Service models. Discover fine-tuning.

GPT-4 updates: Azure OpenAI Service can fine-tune GPT-4. Organizations can customize the AI model by fine-tuning. It’s like customizing an AI suit. Checking GPT-4 updates.

Frontier steering: Prompting power grows

GPT-4 prompting dazzles! Microsoft Research recently blogged about promptbase, a reasoning-based GPT-4 prompt. Other AI models lag behind GPT-4 in various test sets, including those used to benchmark the recently announced Gemini Ultra. Zero-shot chain-of-thought prompting. See the blog post and try these GitHub resources.

LLMOps RAI tools and practices

Safety boundaries supporting short- and long-term ROI must be considered as AI adoption matures and companies produce AI apps. This month’s LLMOps for business leaders article covered integrating responsible AI into your AI development lifecycle. These Azure AI Studio best practices and tools help development teams apply their principles.

AI Advantage from Azure

Cloud database Azure Cosmos DB uses AI. Built-in AI, natural language queries, vector search, and simple Azure AI Search integration are supported. To demonstrate these benefits, her new Azure AI Advantage offer gives new and existing Azure AI and GitHub Copilot customers 40,000 RU/s of Azure Cosmos DB for 90 days.

Modern data and analytics platforms are essential for AI transformation because intelligent apps need data.

Multinational law firm Clifford Chance benefits clients with new technology. The company built a solid Azure data platform to test Azure AI, Microsoft 365 Copilot, and large language models. Cognitive translation is an IT team’s fastest-growing product.

Azure Machine Learning and Azure Databricks helped Belgian insurance company Belfius reduce development time, efficiency, and reliability. Data scientists can create and transform features while the company improves fraud and money laundering detection.

Co-innovation Azure-Databricks improves AI experiences

Customers and partners shared how maturing AI tools and services are helping them achieve more at Microsoft Ignite 2023 in November.

One of her strategic partners, Databricks offers Azure’s fastest-growing data services. Azure Databricks’ interoperability with Microsoft Fabric and use of Azure OpenAI to improve customer AI experiences were recently demonstrated. Customers can build retrieval-augmented generation (RAG) applications on Azure Databricks and analyze the output with Power BI in Fabric using Azure OpenAI LLMs.

Azure Database PostgreSQL AI extension

With the new Azure AI extension, Azure OpenAI LLMs can generate vector embeddings and build rich PostgreSQL generative AI applications. These powerful new capabilities and pgvector support make Azure Database for PostgreSQL another great place to build AI-powered apps.

SQL Server anywhere gets Azure Arc cloud innovation

SQL Server manageability and security improvements from Azure Arc are available this month. Customers can optimize database performance and gain critical SQL Server estate insights with SQL Server monitoring. Azure portal makes Always On availability groups, failover cluster instances, and backups more visible and simple.

Lower Azure SQL Database prices Calculate hyperscale

The new Azure SQL Database price Hyperscale gives cloud-native workloads Azure SQL performance and security at commercial open-source database prices. For scalable, AI-ready cloud applications of any size and I/O, hyperscale customers can save 35% on compute resources.

Apps change operations and experiences

Personalized employee apps and customer chatbots are examples of digital applications developed and deployed by companies using AI to improve operations and experiences. Updates like these enable innovation.

Custom copilots and the seven AI development pillars

Copilots are exciting, and Azure AI Studio in public preview lets developers build generative AI apps. Businesses must carefully design a durable, adaptable, and effective approach for this new era. What can AI developers do for customer engagement? Consider these seven pillars for your custom copilot.

AKS is a top cloud-native intelligent app platform

AI and Kubernetes will influence app development. AI and cloud-native collaboration drives innovation at scale, with Azure Kubernetes Service (AKS) supporting compute-intensive workloads like AI and machine learning. Brendan Burn’s KubeCon blog describes how Microsoft builds and supports customer-beneficial open-source communities.

Azure enables unlimited innovation.

Her recent portfolio news, resources, and features, especially digital applications, have received great tech community and customer response.

Ignite’s Platform Engineering Guide is a hit, demonstrating demand for this training. 

Technology innovation in companies is crucial.  

Two recent customer stories caught my eye.

Modernizing LEGO House interactive experiences with Azure Kubernetes

Here helping The LEGO House in Denmark, the ultimate LEGO experience center for kids and adults, migrate custom-built interactive digital experiences from an aging on-prem data center to Microsoft Azure Kubernetes Service (AKS) to improve stability, security, and iteration and collaboration on new guest experiences. LEGO House updates experiences faster with this cloud move and guest feedback. The modernizing destination hopes to share knowledge and technology with LEGOLAND and brand retail stores.

Gluwa chose Azure for a reliable, scalable cloud solution to bring banking to emerging, underserved markets and close the financial gap.

An estimated 1.4 billion people struggle to get credit or personal and business loans in a country with limited financial infrastructure. Borderless financial technology from blockchain helps Gluwa with Creditcoin stand out. The Azure cloud supports it. Gluwa has a solid platform with her.NET framework, Azure Container Instances, AKS, Azure SQL, Azure Cosmos DB, and more. The business is more efficient due to reliable uptime, stable services, and rich product offerings.

CARIAD builds Volkswagen Group vehicle service platform with Azure and AKS

The Volkswagen Group’s software subsidiary CARIAD created the CARIAD Service Platform with Microsoft using Azure and AKS to provide automotive applications to Audi, Porsche, Volkswagen, Seat, and Skoda as the industry moved to software-defined vehicles. This platform lets CARIAD developers develop and service vehicle software, giving Volkswagen an edge in next-generation automotive mobility.

AKS and Azure Arc help DICK’S Sporting Goods provide omnichannel service

To create a more consistent, personalized customer experience across its 850 stores and online retail experience, DICK’S Sporting Goods envisioned a “one store” technology strategy to write, deploy, manage, and monitor its store software across all locations nationwide and reflect those experiences on its eCommerce DICK’S needed modularity, integration, and simplicity to integrate its public cloud and edge computing systems.

DICK’s Sporting Goods is using Azure Arc and Azure Kubernetes Service to migrate its on-premise infrastructure to Azure and create an adaptive cloud environment. The retailer can now easily deploy new apps to every store for ubiquity.

Performance and efficiency of Azure Cobalt for intelligent apps

Azure has hundreds of cloud-native and intelligent application performance services. Azure silicon performance and efficiency efforts have expanded. Azure Maia, her first custom AI accelerator series for cloud-based AI training and inference, and Azure Cobalt, her first Microsoft Cloud CPU, were launched recently.

Azure Arm chips perform 40% slower than Cobalt 100, the first 64-bit 128-core chip in the series, which runs Microsoft Teams and Azure SQL.

Read more on Govindhtech.com

[autoexplored]

TVS Unveils 2024 Apache RTR 160 4V at MotoSoul 2023 Festival with Exciting Upgrades

TVS Motor Company has set the stage on fire at the MotoSoul 2023 motorcycle and music festival with the grand launch of the 2024 TVS Apache RTR 160 4V. Priced at an attractive ₹1.35 lakh (ex-showroom), the new model comes packed with enhancements that promise an elevated riding experience for enthusiasts. Upgrades for the New Model Year: The 2024 Apache RTR 160 4V boasts several key upgrades,…

[foresight-opinion-trading]

ChatGPT was just the beginning, here are 5 examples from OpenAI Dev Day that will blow your mind!

It's only been 24 hours since OpenAI released their new product GPTs.OpenAI has once again taken the tech world by storm, introducing a slew of groundbreaking innovations during their Dev Day event that promise to reshape the future of AI and human-machine interaction. It's been a mere 24 hours since the launch of their latest product, GPT-3, and the possibilities seem endless. Let's delve into five jaw-dropping examples that will undoubtedly leave you in awe. https://aieventx.com/revolutionizing-personalized-ai-introducing-customizable-chatgpts/

1. The AI assistant travel app

he first revelation that has garnered significant attention is an AI-powered travel app. This app leverages the remarkable capabilities of GPT to assist travelers in planning their journeys like never before. From suggesting personalized itineraries to providing real-time language translation and local insights, this AI assistant promises to revolutionize the way we explore the world. Check out a sneak peek here https://twitter.com/steventey/status/1721727649473868129 Beyond the innovations themselves, it's essential to appreciate the broader implications of these advancements. The introduction of an AI-powered travel app, for instance, not only streamlines the travel planning process but also holds the potential to bridge language barriers and foster a deeper cultural understanding among travelers. It opens up opportunities for more immersive and enriching experiences in an increasingly interconnected world.

2. GPT-4V + TTS = AI Sports narrator

Sports enthusiasts have a lot to cheer about with OpenAI's GPT-4V. This innovative combination of GPT technology and Text-to-Speech (TTS) functionality enables the creation of AI sports narrators that can provide real-time commentary, analysis, and even emotion-infused reactions during live games. Sports broadcasting may never be the same again. https://twitter.com/geepytee/status/1721705524176257296 The fusion of GPT technology and Text-to-Speech in the realm of sports narration not only promises to elevate the quality of sports broadcasting but also democratizes the access to sports commentary. This innovation could make sporting events more accessible to individuals with visual impairments or those who speak different languages, fostering inclusivity in the world of sports.

3. GPT Builder:

OpenAI is expanding the horizons of creativity with GPT Builder. This tool opens up new possibilities for content creators and developers by allowing them to instruct and generate specific content through natural language instructions. Whether you're crafting code, designing graphics, or composing music, GPT Builder promises to be an indispensable companion. https://twitter.com/rowancheung/status/1721644987044294961 GPT Builder, with its ability to generate content based on natural language instructions, has the potential to revolutionize various industries. Developers can streamline their workflow, content creators can ideate more efficiently, and educators can provide personalized learning experiences. The applications are boundless.

4. Increased Context Length 128k

For those who crave deeper and more context-rich conversations with AI, OpenAI has extended the context length of their models. This enhancement enables more coherent and detailed exchanges with the AI, making it even more versatile for complex tasks and discussions. Discover the difference here https://twitter.com/_amankishore/status/1721647536312869040 The extension of context length in OpenAI models marks a significant stride in natural language understanding. It enables AI systems to comprehend and respond to more extended and intricate conversations, paving the way for enhanced customer support, more sophisticated chatbots, and even more meaningful virtual companions

5. Roast My Website

I've come across an impressive project called "Roast My Website" that utilizes the newly announced OpenAI APIs. With the power of GPT-4 Vision, it analyzes website screenshots and delivers humorous roasts. Additionally, the recently introduced text-to-speech API transforms these roasts into engaging audio content, adding a whole new level of entertainment and feedback to web design. You can get a taste of this innovative project here https://twitter.com/marcelpociot/status/1721672359566799070 . "Roast My Website" may appear whimsical, but it serves as a testament to the versatility of AI in providing engaging and entertaining interactions. By infusing humor into AI interactions, OpenAI showcases the potential for AI to enhance our daily lives beyond practical utility.

Conclusion

OpenAI's Dev Day has undeniably heralded a new era of AI innovation, pushing the boundaries of what's possible ever further. These groundbreaking developments leave us wondering what incredible applications and advancements the future holds. The journey of human-AI collaboration has only just begun, and OpenAI stands as a pioneering force on this thrilling frontier. Stay tuned for more mind-blowing innovations that are sure to redefine our interactions with AI. The innovations presented during OpenAI Dev Day offer a glimpse into a future where AI seamlessly integrates into our lives, enriching our experiences, and augmenting our capabilities. The rapid pace of development in AI continues to astound, and as we embrace these advancements, we can anticipate a world where human-AI collaboration unlocks new realms of possibility. The future, it seems, is indeed great, and OpenAI is leading the charge into this exciting frontier. Read the full article

[tvsnotor]

rtr 2v 4v fi abs apache rtr 2v apache rtr 4v tvs rtr 160 4v tvs apache 4v 4v apache apache 4v new version price in bangladesh 4v new model rtr 160 4v rtr 4v tvs 4v 4v bike apache rtr 160 2v

[tvs1]

EXPLORE BHARATH TVS SHOWROOM IN BANGALORE FOR TVS BIKES

The Bharath TVS showroom is the perfect place to start your search for your ideal TVS two-wheeler if you're looking for a TVS showroom in Bangalore and are as passionate about two-wheelers as I am. Renowned Indian motorcycle maker TVS Motor Company is well-known for producing high-performing and inventive two-wheelers. I'll take you on a virtual tour of the Bharath TVS dealership in Bangalore with me in this blog post. There, we can look at a wide variety of TVS bikes, all of which may be customized to suit different riding demands and preferences.

LOCATION AND AMBIANCE:

 I am immediately struck by the Bharath TVS showroom's excellent placement in a well-known neighborhood in Bangalore. It is very accessible, which is fantastic for people who share my passion for motorcycles. The large, well-lit layout of the showroom

GROUP OF PRODUCTS:

The wide selection of TVS two-wheelers at the Bharath TVS store is one of its most notable qualities. Whether I'm an experienced rider or a novice searching for my first ride, I'm sure I'll find everything I need right here.

TVS Apache Series: 

The TVS Apache RTR 160 4V and Apache RR 310 are two models in the Apache series, which is renowned for its aggressive and sporty styling. These bikes provide great performance, cutting-edge features, and an exhilarating ride.

TVs Ntorq Series: The TVS Ntorq series is a standout for scooter enthusiasts like myself who enjoy a sporting edge.

TVS Moped: Mopeds are often equipped with fuel-efficient motors, making them ideal for daily travel. These two-wheelers are simple to operate and maintain, making them an excellent choice for new riders like me or those on a tight budget.

TVS iQube: The iQube is an electric scooter that combines cutting-edge technology with environmental responsibility. It provides an environmentally beneficial and silent riding experience, contributing to a cleaner environment. The iQube is intended for urban transportation, with a sleek and modern design and powerful networking features that allow riders like me to stay connected while on the move.

https://bharathtvs.com/tvs-showroom-in-bangalore/

[tvsturkey]

TVS Motor: All Set to Launch Euro-5 Compliant Two-Wheelers in Turkey

Introduction

TVS Motor, one of India's leading two-wheeler manufacturers, is all set to launch a range of Euro-5 compliant two-wheelers in Turkey in March 2023. This is a significant development for the company, as Turkey is one of its key markets outside of India.

Euro-5 emission standards for motorcycles and scooters are scheduled to be implemented in Turkey starting in 2024. This means that all new two-wheelers sold in Turkey after this date must comply with the new standards.

TVS Motor has been preparing for the launch of Euro-5 compliant two-wheelers in Turkey for several months. The company has invested in research and development to develop new engines and technologies that meet the new emission standards.

TVS Motor's range of Euro-5 compliant two-wheelers for Turkey will include En iyi motosiklet models like the Jupiter, NTORQ Race Edition, Raider, and Apache RTR 200 4V. These models are all popular with Turkish consumers due to their fuel efficiency, performance, and affordability.

The launch of Euro-5 compliant two-wheelers is expected to boost TVS Motor's sales in Turkey. The company is targeting a market share of 20% in the Turkish two-wheeler market by the end of 2024.

Benefits of Euro-5 compliant two-wheelers

Euro-5 compliant two-wheelers offer a number of benefits over older models, including:

Reduced emissions: Euro-5 compliant two-wheelers produce significantly lower emissions of pollutants such as nitrogen oxides and hydrocarbons. This helps to improve air quality and reduce the impact on the environment.

Improved fuel efficiency: Euro-5 compliant two-wheelers are more fuel-efficient than older models. This means that riders can save money on fuel and travel further on a single tank.

Better performance: Euro-5 compliant two-wheelers are equipped with more advanced engines and technologies, which results in better performance and handling.

Overall, the launch of Euro-5 compliant two-wheelers by TVS Motor is a positive development for the Turkish two-wheeler market. It will help to improve air quality, reduce fuel costs, and offer riders a better overall riding experience.

The Euro-5 Standard

The Euro-5 standard, also known as Euro-V, is the latest set of emission regulations for motorcycles in Europe. It imposes stricter limits on exhaust emissions, particularly focusing on reducing the levels of harmful pollutants like carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and particulate matter. These regulations aim to curb air pollution, improve air quality, and promote sustainable transportation.

TVS Motor's Commitment to Sustainability

TVS Motor has always been at the forefront of technological innovation and sustainability. Their decision to launch Euro-5 compliant two-wheelers in Turkey aligns with their long-standing commitment to creating eco-friendly, energy-efficient vehicles. By adhering to the Euro-5 standard, TVS Motor is not only complying with international emission norms but also setting a benchmark for the industry.

Entering the Turkish Market

Turkey has emerged as a significant market for two-wheelers in recent years. The nation's bustling urban areas, scenic landscapes, and growing population have contributed to the rising demand for convenient and efficient modes of transportation. TVS Motor recognizes this potential and is keen on expanding its presence in Turkey.

Challenges and Innovations

Developing Euro-5 compliant two-wheelers comes with its set of challenges. Manufacturers like TVS Motor have had to invest in research and development to redesign engines and exhaust systems to meet the stricter emission standards. This innovation has resulted in more advanced technologies and cleaner engines, ultimately benefiting the environment.

TVS Motor's Euro-5 Compliant Models

TVS Motor has introduced several Euro-5 compliant models tailored to the Turkish market. These include motorcycles and scooters designed to cater to a diverse range of consumer preferences and requirements. The models are equipped with state-of-the-art technology and features, ensuring a comfortable and eco-friendly riding experience.

Local Assembly and Production

To strengthen their presence in Turkey, TVS Motor has considered the option of local assembly and production. This not only demonstrates their commitment to the Turkish market but also aligns with their strategy to minimize carbon emissions associated with transportation during manufacturing and distribution.

Competing in the Turkish Market

TVS Motor is not alone in its ambition to conquer the Turkish market. It faces competition from local manufacturers and other global giants in the two-wheeler industry. However, the company's reputation for innovation, quality, and eco-friendliness is likely to give them a competitive edge.

Collaboration and Partnerships

In a globalized world, partnerships play a crucial role in the success of any venture. TVS Motor has sought collaboration with local dealers, distributors, and service providers in Turkey to ensure seamless customer support and service. Building strong relationships within the local market is essential for long-term success.

Market Penetration and Future Prospects

TVS Motor's entry into the Turkish market with Euro-5 compliant two-wheelers is a significant step forward. It not only aligns with global sustainability goals but also contributes to the Turkish economy by creating job opportunities and boosting the local manufacturing sector.

Furthermore, this expansion is expected to pave the way for more international players in the Turkish two-wheeler market. As competition increases, consumers can look forward to a wider variety of choices, ensuring that they get the best value for their money.

Conclusion

TVS Motor's decision to launch Euro-5 compliant two-wheelers in Turkey is not just a business expansion; it's a statement of commitment to the environment, innovation, and customer satisfaction. The company's focus on sustainability and advanced technology is set to revolutionize the Turkish two-wheeler market, offering consumers eco-friendly transportation options with enhanced performance.

As TVS Motor embarks on this exciting journey, it is likely to face challenges, but with their track record of success and their strong commitment to sustainability, they are well poised to make a significant impact in the Turkish market. This move not only reinforces TVS Motor's global presence but also contributes to a cleaner, greener, and more sustainable world.

[jcmarchi]

📝 Guest Post: Will Retrieval Augmented Generation (RAG) Be Killed by Long-Context LLMs?*

New Post has been published on https://thedigitalinsider.com/guest-post-will-retrieval-augmented-generation-rag-be-killed-by-long-context-llms/

📝 Guest Post: Will Retrieval Augmented Generation (RAG) Be Killed by Long-Context LLMs?*

Pursuing innovation and supremacy in AI shows no signs of slowing down. Google revealed Gemini 1.5, just months after the debut of Gemini, their large language model (LLM) capable of handling contexts spanning up to an impressive 10 million tokens. Simultaneously, OpenAI has taken the stage with Sora, a robust text-to-video model celebrated for its captivating visual effects. The face-off of these two cutting-edge technologies has sparked discussions about the future of AI, especially the role and potential demise of Retrieval Augmented Generation (RAG).

Will Long-context LLMs Kill RAG?  

The RAG framework, incorporating a vector database, an LLM, and prompt-as-code, is a cutting-edge technology that seamlessly integrates external sources to enrich an LLM’s knowledge base for precise and relevant answers. It is a proven solution that effectively addresses fundamental LLM challenges such as hallucinations and lacking domain-specific knowledge.

Witnessing Gemini’s impressive performance in handling long contexts, some voices quickly predict RAG’s demise. For example, in a review of Gemini 1.5 Pro on Twitter, Dr. Yao Fu boldly stated, “The 10M context kills RAG.” 

Is this assertion true? From my perspective, the answer is “NO.” The development of the RAG technology has just begun and will continue to evolve. While Gemini excels in managing extended contexts, it grapples with persistent challenges encapsulated as the 4Vs: Velocity, Value, Volume, and Variety.

LLMs’ 4Vs Challenges

Velocity: Gemini faces hurdles in achieving sub second response times for extensive contexts, evidenced by a 30-second delay in responding to 360,000 contexts. Despite optimism about LLMs’ computational advancements, speedy responses at the sub second level when retrieving long contexts remain challenging for large transformer-based models.

Value: The value proposition of LLMs is undermined by the considerable inference costs associated with generating high-quality answers in long contexts. For example, retrieving 1 million tokens of datasets at a rate of $0.0015 per 1000 tokens could lead to substantial expenses, potentially amounting to $1.50 for a single request. This cost factor renders such high expenditures impractical for everyday utilization, posing a significant barrier to widespread adoption.

Volume: Despite its capability to handle a large context window of up to ten million tokens, Gemini’s volume capacity is dwarfed when compared to the vastness of unstructured data. For instance, no LLM, including Gemini, can adequately accommodate the colossal scale of data found within the Google search index. Furthermore, private corporate data will have to stay within the confines of their owners, who may choose to use RAG, train their own models, or use a private LLM.

Variety: Real-world use cases involve not only unstructured data like lengthy texts, images, and videos but also a diverse range of structured data that may not be easily captured by an LLM for training purposes such as time-series data, graph data, and code changes. Streamlined data structures and retrieval algorithms are essential to process such varied data efficiently.

All these challenges highlight the importance of a balanced approach in developing AI applications, making RAG increasingly crucial in the evolving landscape of artificial intelligence. 

Strategies for Optimizing RAG Effectiveness

While RAG has proven beneficial in reducing LLM hallucinations, it does have limitations. In this section, we’ll explore strategies to optimize RAG effectiveness to strike a balance between accuracy and performance to make RAG systems more adaptable across a broader range of applications.

Enhancing Long Context Understanding

Conventional RAG techniques often rely on chunking for vectorizing unstructured data, primarily due to the size limitations of embedding models and their context windows. However, this chunking approach presents two notable drawbacks. 

Firstly, it breaks down the input sequence into isolated chunks, disrupting the continuity of context and negatively impacting embedding quality. 

Secondly, there’s a risk of separating consecutive information into distinct chunks, potentially resulting in incomplete retrieval of essential information.

In response to these challenges, emerging embedding strategies based on LLMs have gained traction as efficient solutions. They boast better embedding capability and support expanded context windows. For instance, SRF-Embedding-Mistral and GritLM7B, two best-performing embedding models on the Huggingface MTEB LeaderBoard, support 32k-token-long contexts, showcasing a substantial improvement in embedding capabilities. This enhancement in embedding unstructured data also elevates RAG’s understanding of long contexts. 

Another effective approach to tackle the challenges above is the recently released BGE Landmark Embedding strategy. This approach adopts a chunking-free architecture, where embeddings for the fine-grained input units, e.g., sentences, can be generated based on a coherent long context. It also leverages a position-aware function to facilitate the complete retrieval of helpful information comprising multiple consecutive sentences within the long context. Therefore, landmark embedding is beneficial to enhancing the ability of RAG systems to comprehend and process long contexts.

The architecture for landmark embedding. Landmark (LMK) tokens are appended to the end of each sentence. A sliding window is employed to handle the input texts longer than the LLM’s context window. Image Source: https://arxiv.org/pdf/2402.11573.pdf 

This diagram compares the Sentence Embedding and Landmark Embedding methods in helping RAG apps answer questions. The former works with the chunked context, which tends to select the salient sentence. The latter maintains a coherent context, which enables it to select the right sentence. The sentences in red are answers retrieved by the two embedding methods, respectively. The RAG system that leveraged Sentence embedding gave the wrong answer, while the Landmark embedding-based RAG gave the correct answer. Image source: https://arxiv.org/abs/2402.11573 

Utilizing Hybrid Search for Improved Search Quality

The quality of RAG responses hinges on its ability to retrieve high-quality information. Data cleaning, structured information extraction, and hybrid search are all effective ways to enhance the retrieval quality. Recent research suggests sparse vector models like Splade outperform dense vector models in out-of-domain knowledge retrieval, keyword perception, and many other areas. 

The recently open-sourced BGE_M3 embedding model can generate sparse, dense, and Colbert-like token vectors within the same model. This innovation significantly improves the retrieval quality by conducting hybrid retrievals across different types of vectors. Notably, this approach aligns with the widely accepted hybrid search concept among vector database vendors like Zilliz. For example, the upcoming release of Milvus 2.4 promises a more comprehensive hybrid search of dense and sparse vectors. 

Utilizing Advanced Technologies to Enhance RAG’s Performance

In this diagram, Wenqi Glantz listed 12 pain points in developing a RAG pipeline and proposed 12 corresponding solutions to address these challenges. Image source: https://towardsdatascience.com/12-rag-pain-points-and-proposed-solutions-43709939a28c 

Maximizing RAG capabilities involves addressing numerous algorithmic challenges and leveraging sophisticated engineering capabilities and technologies. As highlighted by Wenqi Glantz in her blog, developing a RAG pipeline presents at least 12 complex engineering challenges. Addressing these challenges requires a deep understanding of ML algorithms and utilizing complicated techniques like query rewriting, intent recognition, and entity detection.

Even advanced models like Gemini 1.5 face substantial hurdles. They require 32 calls to achieve a 90.0% accuracy rate in Google’s MMLU benchmark tests. This underscores the nature of maximizing performance in RAG systems.

Vector databases, one of the cutting-edge AI technologies, are a core component in the RAG pipeline. Opting for a more mature and advanced vector database, such as Milvus, extends the capabilities of your RAG pipeline from answer generation to tasks like classification, structured data extraction, and handling intricate PDF documents. Such multifaceted enhancements contribute to the adaptability of RAG systems across a broader spectrum of application use cases.

Conclusion: RAG Remains a Linchpin for the Sustained Success of AI Applications. 

LLMs are reshaping the world, but they cannot change our world’s fundamental principles. The separation of computation, memory, and external storage has existed since the inception of the von Neumann architecture in 1945. However, even with single-machine memory reaching the terabyte level today, SATA and flash disks still play crucial roles in different application use cases. This demonstrates the resilience of established paradigms in the face of technological evolution.

The RAG framework is still a linchpin for the sustained success of AI applications. Its provision of long-term memory for LLMs proves indispensable for developers seeking an optimal balance between query quality and cost-effectiveness. In deploying generative AI by large enterprises, RAG is a critical tool for cost control without compromising response quality.

Just like large memory developments cannot kick out hard drives, the role of RAG, coupled with its supporting technologies, remains integral and adaptive. It is poised to endure and coexist within the ever-evolving landscape of AI applications. 

*This post was originally published on Zilliz.com here. We thank Zilliz for their insights and ongoing support of TheSequence.

[bikekharidoblogs]

RE Himalayan 452 Easily Clocks Over 140 km/h – VIDEO

The brand new liquid-cooled 450cc engine on RE Himalayan 450 is more likely to kick out round 40 bhp and 35 Nm, mated to a 6-speed gearbox

Royal Enfield is on a mission to have an intensive range of model based on three main powertrains. We’ve got seen how huge RE’s 350cc portfolio has develop into and 650cc portfolio is turning into.

However Royal Enfield is but to launch model on its new 450cc engine. A Himalayan 450 take a look at mule is noticed with panniers and different equipment, cruising at speeds over 140 km/h.

You may like it : Royal Enfield Himalayan 452 officially unveiled

RE Himalayan 450 have incredible cruising speeds?

Himalayan 450 ADV would be the one to debut this new 450cc engine that Royal Enfield has been growing for a very long time. It has a liquid-cooling jacket together with a big radiator to dissipate heat and it appears prefer it has a DOHC setup as effectively.

4V head will in all probability be within the combine and the expected output from this engine is round 40 bhp and 35 Nm.

How these expected figures translate into real life, is slightly attention-grabbing. In a current video by Bunny Punia YouTube channel, we are able to see a RE Himalayan 450 take a look at mule outfitted with two exhausting panniers and a top box.

These equipment will be sold separately as a part of accessories. These accessories usually are not the attention-grabbing a part of this video.

This take a look at mule was cruising at very high speeds. Bunny Punia recorded this take a look at mule from a Nissan Magnite AMT on a highway. As seen within the video below, mentioned Magnite was doing 140 km/h (indicated speed within the instrument cluster) and Himalayan 450 take a look at mule pulled away from the spying car.

While we were doing 140 on our speedometer, the bike kept pulling away + the rider was sitting upright and not crouching down + panniers don’t help in slicing through air.

You may like it : Best Bikes in India 2023

That is an impressive feat for Royal Enfield Himalayan 450 because it displays the bike’s high-speed cruising abilities. Being an ADV and a touring bike, this high-speed cruising means is a solid addition to its belt. Main rivals can be upcoming KTM 390 Journey and Triumph Scrambler 400X.

You may like it : Best Electric Bikes in India

What to expect?

Speedometers in vehicles do comprise some errors. OEM-equipped speed sensors are sometimes enthusiastic and normally present the next number.

Therefore, there exist specialist timing gears that may file correct vehicular speeds primarily based on GPS, calculating velocity over a distance and translating into set speed indications. I personal a contemporary Hyundai vehicle and it normally shows 10 km/h increased indicated speed.

Stated Nissan Magnite AMT may have an enthusiastic speedometer as effectively. So, if we contemplate a margin of error, it might be travelling at round 10 km/h to 15 km/h slower than the indicated pace.

So, RE Himalayan 450 could probably hit 130 km/h with comparatively low stress after which some. Which continues to be impressive contemplating air drag from two panniers and an upright rider.

Upcoming Himalayan 450 is rumoured to function a 6-speed gearbox and would possibly pack a slipper clutch and ride-by-wire throttle, enabling cruise management.

What it’ll offer are, wire-spoke wheels, long-travel suspension, dual-purpose tyres, USD telescopic forks at front and rear mono-shock suspension setup, a tall windscreen, and a completely digital circular instrument screen that additionally featured on Scram 650 take a look at mule. Launch is likely in early 2024.

You may like it : Himalayan 450 pics and expected launch date leaked!

[vlruso]

Unlocking Multimodal AI with Open AI: GPT-4Vs Vision Integration and Its Impact

📢 Introducing Open AI's GPT-4V: the next level of AI! 🌟 With vision integration, this language model analyzes images alongside text, unlocking new opportunities and challenges. 🌐 Find out how it works and its impact here: https://ift.tt/Wvotjzu. #AI #GPT4V #OpenAI List of Useful Links: AI Scrum Bot - ask about AI scrum and agile Our Telegram @itinai Twitter -  @itinaicom