Saral Jain

Using generative AI, NVIDIA operations built an AI Planner agent, developed on NVIDIA Inference Microservices (NIM). The agent leverages LLM, NeMo Retriever and CuOpt NIM to reduce re-planning time from hours to just seconds. https://nvda.ws/4bIfS2T

3

Using generative AI, NVIDIA operations built an AI Planner agent, developed on NVIDIA Inference Microservices (NIM). The agent leverages LLM, NeMo Retriever and CuOpt NIM to reduce re-planning time from hours to just seconds. https://nvda.ws/4bIfS2T

2

SEMICON WEST is on fire 24x7 Tuesday afternoon continued the focus on Front-End Manufacturing. Great session on wafer map visual analytics with Janhavi Giri, Intel, using self-supervised learning for image analysis, detecting failures and optimizing manufacturing processes. Naor Alfassi, Applied Materials, spoke about ML-guided Electron Beam review for wafermap image classification and defect detection. Janhavi Giri, PhD Naor Alfassi Sessions on virtual metrology from Srividya Jayaram, Siemens, on high product mix; and Mike Yim, Gauss Labs, on high-volume, from Lab to Fab. In our experience, virtual metrology has led to massive time savings in product testing.  Srividya Jayaram Mike Young-Han Kim One very fun and topical presentation was from Christoher Nguyen, Aitomatic, and Daisuke Oku, Tokyo Electron - announcing SemiKong, a new Open-Source Semiconductor LLM, jointly developed by Tokyo Electron, Aitomatic, FPT AI Center and the AI Alliance. This seems to be based on Meta's Llama3 with additional HTM context. Christopher Cuong T. Nguyen Daisuke Oku I just returned from visiting our HTM customers in Japan and Korea, where we showed our Spotfire Copilot running in Japanese and Korean .. and this presentation on SemiKong was a joy to see!! Feel free to check out my latest blog on the Japan visit including a Spotfire Seminar with our partner NTT Com and customers including Texas Instruments, Tokyo Electron, Toshiba, Sony and many others. MOC Blog on Spotfire Seminar in Tokyo, Japan https://lnkd.in/gAeSZSSC   Wednesday sessions in Smart Manufacturing focused on how AI/ML can optimize back-end semiconductor manufacturing process eg OEE, predictive and condition-based maintenance.. We are currently revamping our Spotfire OEE solution with Spofire Copilot, so this is quite timely. Shawn Sarbacker, Kulicke and Soffa,  gave a nice presentation on Semiconductor Assembly.  Shawn Sarbacker I really enjoyed the session on Zero Defect Manufacturing from Prasad Bachiraju, Onto Innovation. Totally aligned with our Spotfire work on visual data science for defect analysis .. interesting backend data integration .. we’ve been working on data federation and libraries of virtualization views for that part of the data and analytics flow.  Prasad Bachiraju I also liked the IBM WatsonX GenAI session from Megan Arp and Francois Bernard - many similarities to our Spotfire Copilot e.g. they refer to the “Watson Orchestrator” in an analogous architecture to our Spofire Copilot Orchestrator. Their LLM is able to predict user intent when a technician reviews a ticket (i.e., query vs. task). Tasks are handled through custom and prebuilt skills training, while queries are handled through RAG. Megan Arp Francois Bernard Spotfire #VisualDataScience https://lnkd.in/eSeVcE5h https://lnkd.in/ecWq3PSH

56

3 Comments

We are excited to back Morphing Machines. As Dr. Ranjani, CTO and co-founder says: “For the first time in India and globally, we have a processor that is truly runtime reconfigurable, catering to emerging workloads.” While Nvidia’s growth and high valuation are driven by robust demand for “infra-compute” in high-performance GPUs, spurred by Gen AI, there is a distinct need for innovative solutions tailored to a new wave of reactive applications. Enter Morphing Machines. It addresses this demand with its unique product designed for next-gen telecom, autonomous vehicles, collaborative robots, avionics, and online data analytics. This product is specifically engineered to handle heterogeneous workloads and diverse tasks with varying performance demands simultaneously, ensuring a high level of scalability. As we move from an institutionally-backed research team at IISC to productization, Golden Sparrow is collaborating with Speciale Invest and others to support Deepak Shapeti, who joined as CEO three years ago after earning his Masters at Stanford. He brings not only technical expertise but also the business acumen necessary to guide the product to commercial success. Venkat Raju Afreed Faizan Anand Rao Ritik Singh Michael Marmor

68

5 Comments

From reshaping the future of work to revolutionizing creative endeavors, explore the transformative power of generative AI in everyday life with Tilakraj Parmar, Co-Founder and CEO, QX Lab AI. Discover how AI-powered chatbots are enhancing customer experiences, freeing up time for strategic initiatives. Learn about the creative realm, where AI algorithms are amplifying artistic expression and pushing the boundaries of music, the visual arts, and content creation. According to Tilakraj, a world improved by the peaceful coexistence of human creativity and AI efficiency is in store. 🔗Read the full article exclusively on Express Computer, to unlock the potential of this groundbreaking technology: https://lnkd.in/gAzagtsV   #ai #generativeai #genai #futureofwork #creativity #innovation

13

Ai : Hunanity's greatest creation for Good and Bad. To secure ourself #zerotrustai In the journey, MS brings up VASA-1 will AI model which essentially spins a selfie image and turn it into a talking clip of you. All you have to do is upload a photo along with a voice note and let the AI model do the talking for you.

2

Decoding LLMs: Unveiling the Childlike Nature of Large Language Models My recent wrangling with ChatGPT have led me to a compelling insight, which I shared in an internal session. This particular slide, highlighting the intuitive understanding of LLMs, garnered much praise. I’m excited to share this revelation with a broader audience. #AI #ChatGPT #LanguageModels #TechnologyInsights #LLMAnalogy

36

4 Comments

That’s why we never ask for business plans, 3-5 year financial projections or similar documents in the early days! Who are the founders, what makes them special and how big is the market, that’s it 👌 Beats any “business plan”, business model canvas, or any of the Strategyzer alternative documents IMHO

38

10 Comments

Union.ai just introduced artifacts and reactive workflows. During my time at Meta, we had a similar construct in our DAG orchestration engine where artifacts produced by workflows could be stored/queried, and additional caching mechanisms could be leveraged to reuse artifacts from expensive jobs. Reactive workflows is an innovative and intuitive way to tackle this problem by introducing triggers where a workflow will run automatically when an artifact is published. Exciting work by the Flyte team! https://lnkd.in/gUg78gjA

12

Weekend update: TrialSight AI is now Zeeq AI (rhymes with "seek")! Zeeq (https://zeeq.ai) is an #AI agent inspired by the Clinical Trials Transformation Initiative (CTTI) AACT project that watches FDA ClinicalTrials.gov for the latest updates and emails you a personalized newsletter that answers your questions for trials that match your criteria. Whether you are a patient, researcher, pharma executive, or industry analyst, Zeeq helps you stay on top of the latest developments any time a change is added to ClinicalTrials.gov. The agent is now even faster (see for yourself) and still free to sign up (no usernames or login required). I'm getting close to go-live. The monitoring logic is ready and testing the email generation this morning. Still need to add a passwordless/accountless way to manage the subscriptions.

10

1 Comment

Accelerate the shift to generative #AI! Leverage large language models for AI fine-tuning and inference. Enable new GenAI apps such as text generation, translation, coding, and visual content, and deploy at scale. New video! NVIDIA #HPEProLiant https://hpe.to/604498Rm4

1

Everyone knows Moore’s law, the idea that CPU performance doubles roughly every two years. But remarkably, driven by GPU performance and AI model breakthroughs, we’ve seen a very different law emerge with respect to the rate at which AI model performance improves — in many cases improving by orders of magnitude in the past decade. This introduces massive implications in a world of AI Agents. For the past five plus decades, in any domain that computers touch, we’ve generally seen massive efficiency gains that bring more tech to more people. Yet the same has not been possible for essentially any non-digital services. Historically, anytime you want to solve non-computerized business problems (i.e. most knowledge work), we have seen the cost to solve a problem — say from healthcare services to legal work — tend to only go up over time. Due to a mix of inflation, specialization in certain fields, regulation, decreased competition in markets, or other added costs, we’ve seen the price of most services generally monotonically increase over time. This also puts a burden on driving economic activity in general, especially when creating new ideas from scratch, or starting and running a new business. Yet, in a world of AI Agents, anyone — from a small business or large enterprise — has access to automated work that can let them address problems with variable capacity. When you decrease the cost of entry for getting knowledge work done, you dramatically increase the use cases for that work. That new sales program can be tested instantly instead of waiting weeks or months or never happening at all; you can test a broader surface area of your product for bugs or security issues; legal work and reviews becomes affordable on the seemingly insignificant transactions that otherwise produce risk; or you can launch a new marketing campaign in markets you didn’t otherwise serve. Even in a world of AI costs remaining stable this is a super compelling proposition, but in a world of constantly improving technology the implications are vast. Just as Moore’s law steadily lowered the cost of software, increased its sophistication, and made it more ubiquitous, we can imagine a world where knowledge work regularly gets more affordable, sophisticated, and ubiquitous at a constant rate. This means AI Agents present the ability for any unit of work to continuously drop overtime, enabling us to solve greater and greater problems for a wider set of people and businesses. Of course, a large portion of these efficiency gains will quickly get “eaten up” by solving increasingly more sophisticated problems, but those problems will be solved at the cost of a previously simpler problem. The implications of this are enormously interesting, and it’s going to create incredible opportunities all around.

151

13 Comments

So much fun talking about the power of LLMs with Amazon Bedrock and Anthropic Claude. In summary, the ever-evolving landscape of GenAI, it's becoming clear that there won't be a single LLM (Large Language Model) to rule them all. The rise of application-specific LLMs heralds a new era, where various models will carve out niches to excel in. This diversity opens up a wide playing field for innovation and tailored solutions. When it comes to deploying AI models, striking the right balance in evaluation is paramount. We must weigh factors like cost, speed, and precision to ensure optimal performance and resource utilization. Finding this equilibrium ensures that our GenAI solutions are not just efficient but also effective in real-world scenarios. Anthropic Claude emerges as a frontrunner in the realm of LLMs, distinguished by its exceptional capabilities and groundbreaking advancements. Boasting unparalleled scale, efficiency, and adaptability, Anthropic Claude represents a pinnacle of GenAI innovation. Its ability to seamlessly integrate with Amazon Bedrock amplifies its prowess, providing users with an unparalleled ecosystem for knowledge integration and generation. With state-of-the-art architecture and a commitment to pushing the boundaries of what's possible, Anthropic Claude stands as a testament to the transformative potential of GenAI in shaping the future of technology and beyond. Prompt engineering holds the key to maximizing the potential of applications. Crafting prompts that consider persona, context, tags, and positioning can significantly enhance the model's ability to comprehend and generate relevant responses. This strategic approach empowers AI systems to better serve their intended purposes. In the realm of GenAI architectures, a robust knowledge base is essential. Amazon Bedrock stands out as a key component for architectures like RAG (Retrieval-Augmented Generation), providing a solid foundation to fuel intelligent decision-making and content generation. As we march towards AI integration, bridging the gap with legacy applications is crucial. Agents equipped with open APIs offer a seamless way to facilitate communication and interoperability, ensuring a smooth transition into the AI-driven future. Let's continue to explore, innovate, and collaborate as we navigate the exciting frontier of GenAI together! #aws #LanguageModels #Innovation #TechTrends #AIIntegration #webdevcon #claude #bedrock

68

Using generative AI, NVIDIA operations built an AI Planner agent, developed on NVIDIA Inference Microservices (NIM). The agent leverages LLM, NeMo Retriever and CuOpt NIM to reduce re-planning time from hours to just seconds. https://nvda.ws/4bIfS2T

20

1 Comment

Amazon Bedrock Claude 3.5 Sonnet: Cutting-Edge AI Model at Unbeatable Cost! Claude 3.5 Sonnet opens new possibilities for AI applications by providing robust performance at an affordable cost. Businesses can now deploy advanced AI for various tasks, from data analysis to creative content generation, enhancing efficiency and innovation. This model's versatility and intelligence pave the way for future technological advancements and more sophisticated AI solutions across different industries. https://lnkd.in/e-iDzqAb

2

🚀 The need for India-focused GenAI platforms has led to a host of indigenous developments. Let's take a look at 8 Made-in-India LLMs that are shaping the country's future. 🔸 Recognizing the socio-cultural gap in existing systems, entrepreneurs and developers from India are working on a GenAI ecosystem tailored for Indian consumption, yielding better contextual outputs across all formats. 🔸 A handful of homegrown conglomerates, such as Reliance (Jio), Tata Consultancy Services, Infosys, and Mahindra & Mahindra, are already working on a slew of GenAI projects. 🔸 Indigenous developments like BharatGPT, Ola Krutrim, and Project Indus (a Tech Mahindra venture including 40 different Indic languages), are addressing the language challenges pan-Indian users face in real life and now in the AI world. According to Inc42 data, India’s GenAI market is expected to grow exponentially in the next few years, surpassing $17 Bn by 2030 from $1.1 Bn in 2023, growing at a CAGR of 48%. With BharatGPT and its ilk taking charge and cementing their positions in India’s conversational AI landscape, India is well-prepared for a new era of digital empowerment where language barriers are dissolved and access to information is democratized. 🌟 Thoughts on this trend: Cultural and Linguistic Relevance: These platforms address India's diverse socio-cultural and linguistic nuances, ensuring inclusivity and effectiveness. Local Innovations and Entrepreneurship: Investments by companies like Reliance, TCS, Infosys, and Mahindra & Mahindra highlight India's growing tech ecosystem and global AI positioning. Economic Growth and Opportunities: The rapid expansion of the GenAI market signifies substantial economic opportunities, leading to job creation and skill development. Digital Empowerment and Accessibility: By providing AI-driven solutions in multiple Indian languages, these platforms enhance digital literacy and inclusivity. Addressing Real-World Challenges: Indigenous AI platforms deliver solutions closely aligned with the needs and preferences of the local population, improving customer service, education, and healthcare support. The emergence of India-focused GenAI platforms is a promising development driving technological, economic, and social progress in the country. Let's look forward to a digitally empowered and inclusive future! 🚀🌐 #GenAI #AI #India #DigitalTransformation #Innovation #Technology #BharatGPT #OlaKrutrim #ProjectIndus #DigitalEmpowerment #FutureTech #AIinIndia

28

3 Comments

Read to learn more from Intel about retrieval-augmented generation (RAG), and its impact on the journey toward intelligent and trustworthy #AI. https://lnkd.in/g_rg6j86

1

The AI chip race is a dazzling showdown between the mega-cap chipmakers and a few fearless unicorns sparking a revolution in computing power. Read on, as I outline some impactful AI Accelerator products that stand a chance to play a major role in the creation of the next generation of AI Cloud🚀 #AIChipWars #LLMs #GPUs #TPUs #LPUs #Datacenter #AICloud #AIAccelerators #HPC

16

4 Comments