Ganesh K. Nanaware, MS, MBA’s Post

Excited to be attending my 12th re:Invent, - 10 years as Amazonian and this year, thrilled to be joining as a partner. Computer vision is transforming industries by improving efficiency, safety, and user experiences, from quality control in manufacturing to optimized store layouts in retail, and from traffic management to waste sorting. Its impact extends to public safety, parking optimization, emergency response, and environmental monitoring. However, deploying deep learning models for inference on edge devices that are often limited in computational power, memory and bandwidth requires optimizations like quantization, pruning etc. Blaize specializes in edge inference, offering a fully programmable Application-Specific Integrated Circuit (ASIC) and an SDK that enable efficient, real-time model execution on edge devices. Looking forward to connecting with customers, partners, and former colleagues at re:Invent. Despite a packed schedule, I'll make time to dive deep into how Blaize is disrupting computer vision at the edge and delivering real value to the industry. #edgecomputing #computervision #blaize #ConnectedIntelligence #multimodelswitching #inferenceattheedge Robert Wilson Brian Kurtz Anantha Mohan Kandlakunta

During lunch at the Meta-sponsored Systems@Scale 2024 Conference last week, several attendees discussed the various ML, AI, DL, GenAI, and LLM course offerings out there. There were NVIDIA, Intel, Meta, ASML attendees at our lunch table, working on AI networking infra, inferencing, HPC infra, AI orchestration, AI-augmented chip design frameworks, and enterprise AI + supporting infra projects at respective companies. The consensus seemed to be knowing your goals: Becoming more familiar with the nuts and bolts of AI/ML and its subspaces or becoming more familiar with how to build ML/AI applications and agents. And another consensus seemed to be: Coursera and Stanford Online for general, Cornell ML Certificate Online for the nuts and bolts, MIT and Stanford Online for building apps. A couple of us said that given the time and resources, we would definitely take several courses across the online offerings to build our expertise. It was inspiring and energizing to be among similar minded peers, bouncing our ideas and sharing our learning experience. 😍🤓🐉

Hi LinkedIn network, What an exciting time to be alive! Listening to Dr. Lisa Su alongside pioneering minds like Microsoft's Satya Nadella, HP's Enrique Lores, and Stability.ai's Christian La Forte at COMPUTEX in Taipei provided me with so much food for thought. Dr. Su’s insights into cutting-edge AI and next-gen computing power were truly astonishing. Equally inspiring were the perspectives from Nadella, Lores, and La Forte, each shedding light on the future of technology in their own unique ways. It feels like we’re at the cusp of a technological revolution. From advancements in AI to groundbreaking innovations in computing, the possibilities seem endless. I’m excited about what the future holds and just wanted to share this sense of wonder and anticipation with all of you. Whether you're deeply into tech or just curious about what's next, it's a thrilling time to be part of this journey. On a more curious note, what are you all thinking about when you hear these predictions? Post a comment and lets see what this might mean for all of us :thumbsUp:  #COMPUTEX2023 #Innovation #FutureTech #IncredibleInnovation #TechInspiration https://lnkd.in/gEKdntxg

I am thrilled to share that I have successfully completed the Dell GenAI Foundation exam. It was an enriching journey, deepening my understanding of how AI is shaping human progress and driving business transformation. I extend my heartfelt thanks to Dell Technologies Forum & Events team for providing this incredible learning opportunity. A special note of gratitude to Anay Pathak and Biju Mathew for their guidance and support throughout the process! Keep learning ! #AI #DellTechForum #DriveinnovationWithAI #GenAI

'If you will joining me at HPE Discover in a couple weeks, this is a session you won't want to miss. Join EVP & GM Compute, #HPC and #AI Neil MacDonald at #HPEDiscover to hear how #HPE and NVIDIA are partnering to make this technology more accessible and get insight on where AI is headed. Learn more.' https://hpe.to/6047eIxs9

Having been trained in the era of Moore’s Law, the debate rages on how 3D transistors, backplane power and alternatives materials to silicon will drive chip density. At the software layer parallel coding models will drive performance priority. Given this chip acceleration race; think the market is prime of new innovations to break through to ensure improved performance, lower cost and lower power consumption.

This situation has already occurred for months now. A couple of months ago, during a presentation, I discussed this exact issue. We had a customer who was using AI to lengthen his articles, emails, and other communications. Subsequently, people within his own company were using AI to summarise these articles and emails. I addressed this by teaching them to use AI to make their text shorter, easier to read, and more to the point. This approach saved a considerable amount of token usage, nearly 50% during writing and even more than 50% during reading.

An interesting part of this deal is Anthropic’s agreement to use Amazon’s custom AI chips, Trainium and Inferentia, for training and deploying its models. As Amazon positions its AI hardware as a competitive alternative to NVIDIA GPUs or Google’s TPUs, this strategic move seems very necessary: “If it’s good enough for Anthropic, it’s good enough for you.” Another notable point is the landscape is shifting from “Who owns the biggest model?” to “Who can provide the most competitive ecosystem?” If we are indeed reaching a plateau in foundational model innovation, better infrastructure, tools, and integrations are now more likely to drive the next breakthroughs in AI than bigger models. It’s not easy to stay independent with two giant investors (Amazon and Google). But it might (and hopefully will) lead to a new successful way for AI startups to scale! Any thoughts? __________________ I share my learning journey here. Join me and let's grow together. For more on AI and learning materials, please check my previous posts. Alex Wang #artificialintelligence #technology #machinelearning #innovation #bussiness

ASML Price Target Raised by JPMorgan to $1,207 This compares to a closing price of $840.69 on Friday, Oct. 11. And equates to a 43.5 % upside. ASML Holding N.V. (NASDAQ:ASML) makes and sells advanced semiconductor equipment systems. JPMorgan recently raised the price target on the stock to $1,207 from $1,202 and kept an Overweight rating on the shares. The advisory said the investor base had suddenly gotten very bearish on ASML through the summer. While there were some reasons for this, namely the Intel capex cut, the slow recovery of the consumer semiconductor market and worries about China restrictions on semi cap companies, the long-term bear thesis on ASML was overstated, the advisory told investors in a research note. JPMorgan said that litho intensity in memory would rise because the growth memory was high bandwidth memory which was litho centric. Credit: insider monkey, yahoo finance