Raghu Kopalle

Coeus Institute's GERA, autonomously identified one of the most impactful News of the day under 'Major Business and Finance Update' category. GERA's Innovative Rating algorithm RATED this event ("Street calls of the week: Upgrades for Micron, Magnite and GoodRx Holdings") with a score of 1320.06. GERA's patented rating algorithm automatically identifies critical events, categorizes /classifies them, finds root-causes, discovers correlations, and predicts future events.

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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

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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

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The 7th workshop on Neural Scaling Laws is about to start: https://lnkd.in/gQSB5k8v Scaling laws, emergency, alignment, transfer learning, with a focused track on multilingual models. Looking forward to kick it off with Irina Rish and discuss all these topics with Yuhai Tu, Paul Bogdan, Hailey Schoelkopf, Darshil Doshi, Rio Yokota, Neha Sengupta, Preslav Nakov, Tatiana Shavrina, PhD, Yishi Xu. Join in person or virtually! #icml2024 #ai

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Radical Candor: "If you want to know how a company makes it all the way to market with such an out-of-touch, poorly performing product, the Times interviewed "23 current and former employees, advisers and investors," and their anecdotes shed a lot of light on how this can happen. The two founders apparently "preferred positivity over criticism, leading them to disregard warnings about the AI Pin’s poor battery life and power consumption. A senior software engineer was dismissed after raising questions about the product, they said, while others left out of frustration." After that software engineer was fired for questioning if the AI pin would be ready for launch, the report describes a staff meeting where the founders "said the employee had violated policy by talking negatively about Humane." It's hard to make a good product if you can't honestly talk about the negatives and positives for fear of retaliation. The outside world is not subject to the founders' preferences for "positivity," though. After apparently not being interested in honest employee feedback during development, once the product launched, Bongiorno called the team together and said the company would have to "lean into painful feedback" and called the reviews “a gift that we’ve been given.” The problem with this thinking is that, at this point, the product had launched and received the most attention it would ever get, and nearly all of that was negative. Maybe part of the issue is that the company didn't have a head of marketing until after launch, despite employees "repeatedly asking" for the role to be filled."

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Excited to announce Together Inference Engine 2.0 with new Turbo and Lite endpoints. Today we are announcing a new inference stack, which provides decoding throughput 4x faster than open-source vLLM. Together Inference Engine 2.0 achieves over 400 tokens per second on Meta Llama 3 8B by building on the latest advances from Together AI, including FlashAttention-3, faster GEMM & MHA kernels, innovations in quality-preserving quantization, and speculative decoding. We are also introducing new Together Turbo and Together Lite endpoints that enable performance, quality, and price flexibility so enterprises do not have to compromise. The new endpoints offer the most accurate quantization with Together Turbo closely matching the quality of full-precision FP16 models and available at 10x lower cost than GPT-4o. With Together Lite high-quality AI models are now more affordable than ever, with Llama 3 8B Lite priced at $0.10 per million tokens, 6x lower cost than GPT-4o-mini. These advances make Together Inference the fastest engine for Nvidia GPUs, and the most accurate and cost efficient solution for businesses of all sizes to build with Generative AI at production scale. “Our endeavour is to deliver exceptional customer experience at all times. Together AI has been our long standing partner and with Together Inference Engine 2.0 and Together Turbo models, we have been able to provide high quality, fast, and accurate support that our customers demand at tremendous scale." —Rinshul Chandra, COO, Food Delivery, Zomato No better feeling than customers value-propping your product better than you can ❣ Together Inference Engine 2.0 is officially launched!!! 🚀 🚀 🚀 🚀 Read more here:

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1. IMO, agent patterns are one of the most interesting ways to extend LLMs. memary is based on leveraging a graph database (neo4j) for long-term memory (to get around the limited memory inherent in even the largest context windows in LLMs) and augmenting it with other tools like web search and Computer Vision. https://lnkd.in/gfFcBqJx Looks interesting. 2. More about how consolidation effects the entire healthcare industry: https://lnkd.in/gXJKqNJB The Change hack/ransomware attack not only affected claims, service, refills, etc. but now CMS & NCQA are delaying the entire HEDIS reporting process (used for Medicare/Medicaid quality ratings) due to the impact. 3. NARA bans ChatGPT use agency-wide. https://lnkd.in/gW8T94JU Federal Government agencies see this as a risk, including their information leaking and being used to train models (which may then output the wrong information or show PII/PHI other proprietary information). 4. Oh great, now I can't even be angry anymore :) https://lnkd.in/gcrN9mjx

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Just saw this talk by Jensen Huang, CEO of NVIDIA. He explained the concept of "word to vec," where words are converted into numerical vectors based on their relationships. This process allows for fascinating connections, like mother and father being numerically close, and apples and oranges also being close but far from mother and father. This technique isn't just limited to words—it can be applied to any structured data, like videos, 3D models, proteins, and even genes. By transforming data into vectors, we can translate words to images (like in mid-journey or stable diffusion) or images to words (captioning). The ultimate goal is groundbreaking: turning amino acids into proteins, akin to AlphaFold's achievements. We're in an incredible era of computer science, where converting different forms of information is becoming a reality. #JensenHuang #nvidia #ai #word2vec #DigitalBiology #artificialintelligence #alphafold

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I loved reading this expertly told article; kudos to Yasemin Saplakoglu! It is the story of what might, in hindsight, be remembered as the most impactful innovation driven by machine learning of our time -- and yes, I have heard of that ChatGPT thing ;) (It is an interesting and funny aside that the Alphafold 2 paper talks about #machinelearning, but has zero mentions of #AI.. 😅)

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# Excited to Announce Our Latest Innovation in Data Analytics and Policy Management! I'm thrilled to share that our team at Rakuten Mobile has recently had a patent application published for our "Correlation Engine and Policy Manager (CPE)" system. This innovation represents a significant step forward in how we handle and process event data in complex systems. Patent Details: - Title: Correlation Engine and Policy Manager (CPE), Method and Computer Program Product - Publication No: US 2023/0229461 A1 Key Features: - Efficient event data processing from multiple sources - Real-time data enrichment with business layer information - Dynamic policy application for transformed event data - Automated output dispatch based on policy satisfaction This technology has the potential to revolutionize how businesses handle large-scale data processing and policy implementation, particularly in areas requiring real-time decision making and action. A huge thank you to my co-inventors and the entire team at Rakuten Mobile for their hard work and dedication in bringing this innovation to life. We're excited about the potential impact of this technology and look forward to seeing how it can benefit various industries. #Innovation #PatentApplication #DataAnalytics #TechInnovation #RakuteMobile

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From UC Santa Barbara & Caltech Towards Large Language Models as Copilots for Theorem Proving in Lean P Song, K Yang, A Anandkumar [UC Santa Barbara & California Institute of Technology] (2024) https://lnkd.in/eQA7bWGX - The goal of this work is to explore LLMs as copilots to assist humans in proving theorems, rather than proving theorems fully autonomously without human intervention. - Existing LLM-based provers struggle with truly novel or challenging theorems. Human insights can be critical for such theorems. - The authors introduce Lean Copilot, a framework for running LLM inference in Lean. It allows building various LLM-based proof automation tools like tactic suggestion, proof search, and premise selection. - Lean Copilot enables fast inference of LLMs locally or remotely. It provides general text-to-text generation and text-to-vector encoding interfaces. - Experiments show the effectiveness of tools built using Lean Copilot in assisting humans and automating proofs compared to existing proof automation in Lean. - The work is open-sourced to facilitate research on human-AI collaboration for theorem proving.

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A new research paper by our incredible teams at Google Research and Google DeepMind shows the strong performance of Med-Gemini across a variety of multimodal tasks, including  2D and 3D imaging in radiology, histopathology, ophthalmology, and dermatology, and genomics. Med-Gemini ranked best in class on chest X-ray and CT scan report generation, and is able to perform genomics-based disease prediction and mortality risk more accurately than a standard linear polygenic risk score (PRS) based approach. This work couldn't have been possible without close collaboration with our partners, including a panel of specialists who assessed and rated our models as part of this research. These promising results showcase the potential of LLMs to transform medicine as we know it. https://lnkd.in/dHx8_DYh

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Learn how to develop machine learning applications on the embedded edge from ideation to deployment. Carlos Davila introduces a new framework called Cross-Industry Standard Process for Embedded Machine Learning or CRISP-EML as a new methodology for embedded ML development. He also guides readers through the ML development process by taking into account various stakeholder and persona perspectives. #machinelearning #embeddededge #development #SiMa

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Seismic’s AI enablement assistant, Aura Copilot, is now available for early access. Teams can now get faster access to answers and content, automate tedious tasks, and gain insights for better business decisions. Aura also now integrates with Microsoft Teams and Microsoft 365 Copilot to give teams in-the-moment answers and content recommendation. https://lnkd.in/d_mSbDXK

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Thanks Errol Arkilic for stopping by The Aerospace Corporation. It was great catching up from your days at National Science Foundation (NSF) and hearing about new initiatives at UC Irvine, including the Beal Applied Innovation center and their work partnering with researchers and industry to translate IP into products and markets. Looking forward to following up on those topics! #entrepreneurship

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Just announced by #OpenAI -- read more here: https://lnkd.in/gVsBPRBx Data Analysis is one place OpenAI already really shines thanks to the ADA feature -- can't wait to ee what this adds. #GenAI #AIforBusiness #DataAnalysis

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Join me at #SnowflakeSummit! I'll be on stage with Ellery Berk sharing new #AdvancedAnalytics capabilities in the #DataCloud. Join this session to explore what’s new in #Geospatial data, #TimeSeries, #search optimization, and #MachineLearning with SQL: https://lnkd.in/g-GjvqWr

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Great to see Akash.Network being actively used for AI research! Here (https://lnkd.in/g2Gthb5d) is a recent example of research that proposes "Unified Auto-encoding with masked diffusion" that combines the Diffusion/ Gaussian corruption techniques (used by stable diffusion and others) with Masked Auto-Encoding (MAE) techniques. This technique was verified using infrastructure from Akash (along with google/ GCP)

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