Javier Fernandez Rico

🚀 Looking to streamline fine-tuning for models like Llama 3, Mistral, and Mixtral? Our latest blog shows how Anyscale simplifies LLMs fine-tuning with Ray: 🔑 Key takeaways: • Scalable fine-tuning with LLM-Forge • Model Deployment with RayLLM Read more: https://lnkd.in/gQwD4A2U

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From where I sit in the SF Bay Area, cradle of innovation for at least the last 30 years, I'm a true believer in the promise of the #AI revolution. That said, I find it fascinating to consider views on the opposing side. I'm sharing below two opinion pieces from the last two weeks suggesting that the AI revolution is fundamentally overhyped and a bubble ripe for bursting, and that AI tools are actually not useful or transformative. Contrast this with venture capitalist Kai-Fu Lee's prognostication that 50% of white collar jobs will be displaced by #AI within three years, and that OpenAI and the other cutting edge movers in the space are headed to a trillion+ dollar valuation. Which side will win out? Where will we be by 2030 in the AI race? I'd love to hear your thoughts in the comments.

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#AI is both over-hyped and under-hyped. Over-hyped in the sense that I don't believe artificial general intelligence (AGI) is imminent. Yann LeCun had a great interview in Wired where he outlined why (and dropped a great quote - "Machine Learning Sucks"). https://lnkd.in/exv35XGT Under-hyped in the sense that ROI is already hiding within existing business processes - someone just needs to do the work of re-thinking, re-designing and re-building with an AI first mindset. Friday, April 19th at 11:30am, join me at the River Club (https://lnkd.in/evs8XsYB) with the First Coast Tiger Bay Club for lunch, a short presentation and some q&a. To RSVP, email [email protected]. The event is open to everyone, and $35 for lunch for non-members. Socrates Rivers

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Realistic 3D shapes from text prompts? MIT researchers cracked the code. Their simple fix to Score Distillation enables sharper, higher-quality 3D models without costly retraining or complex postprocessing. This could revolutionize virtual reality, filmmaking, and engineering design. Are you ready for the 3D AI revolution? #GenerativeAI #3DModeling #ComputerVision #AIInnovation #FutureOfDesign What 3D creations would you bring to life with this technology?

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Adversarial Diffusion Distillation (ADD) is a groundbreaking method for ultra-fast, high-fidelity image synthesis! ADD combines the strengths of diffusion models and GANs, generating stunning images in just 1-4 steps. This new approach significantly outperforms existing few-step methods, achieving state-of-the-art quality with unmatched speed.   Paper: https://lnkd.in/dxEAxqu8

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AI's hallucination problem is more than just a glitch - it's a 41% error rate that's holding back real-world applications. Enter knowledge graphs and GraphRAG: powerful tools grounding AI in facts and relationships, making outputs more accurate and explainable. For businesses seeking to harness AI's potential, this could be the key to unlocking trusted, practical solutions. #AIHallucinations #KnowledgeGraphs #AIAccuracy #EnterpriseAI #InnovationInTech What steps is your organization taking to improve AI reliability?

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NVIDIA's Q3 visualized. How long can the boom last? 📊 Revenue trends. 🤖 The 'age of AI' in full steam. 🎙️ CEO Jensen Huang on AI scaling. 👉 Dive into the full article below 👇 https://lnkd.in/gVEDgDyX

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[Crafting Production-Grade Prompts for Agents] Join us on Aug 3 from 2-5 PM for an in-depth workshop on crafting production-grade prompts for AI agents. Learn the intricacies of prompt engineering and create effective prompts for real-world applications. https://buff.ly/3SsMJRE

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There are many variations of the "Nvidia CEO Jensen Huang..." meme at this point on LinkedIn, so here's a different take: Nvidia was a company that was incredibly lucky that their R&D happened to neatly dovetail with the needs of machine learning. For many years, only PC builders like me cared about the classic Nvidia vs. AMD GPU performance battles, and in that context, most of us were only looking at gaming benchmarks. (*Insert "Can it run Crysis?" meme here*) Then one day, a bunch of Bitcoin Bros with Vapes™ drove up the price of the GPU market because they thought consuming the same amount of energy as the entire Philippines was a good idea to solve math problems. Those math problems were stored in digital-coin form, so international crime syndicates could easily launder money. When money laundering fell out of favor, someone convinced impressionable Technology Influencers with Vapes™ that digital Beanie Babies would be worth hundreds of thousands of dollars someday. So if you buy this JPG of a cartoon ape, all you need to take your actual REAL money and turn it into worthless math problems to buy cartoon apes. What could possibly go wrong? How do you solve those math problems to convert valuable USD into fake money to buy cartoon apes so crime syndicates can continue generating revenue? With an entire server room filled with Nvidia GPU's of course! Then, circa 2021 people got wise. "Wait a second, this s**t isn't real money, and I can still just download this JPG. Also, my grandma just got a call from some dude in India who convinced her to convert her Social Security into BTC and send it to an 'Amazon Refund Department' and literally nothing can be done about it. This sucks." People started dumping their GPU's on the open market. Thankfully, this mega-surge in now cheap GPU's allowed AI researchers to pick them up for pennies on the dollar. When Bitcoin Bros with Vapes™ lose, society wins. Suffice to say, yes Nvidia CEO Jensen Huang seems like a good leader and a smart dude, but his management style isn't really what drove Nvidia to success. All those R&D bucks spent accelerating CUDA cores for gaming nerds just happened to line up with the needs of AI/ML engineers. I know this, because I remember when Jensen Huang would do his big keynotes talking about how Nvidia GPU's performed on different gaming and productivity workloads. (Usually graphic designers or video editors.) The attached photo is an old lady sending money to a scammer on a Bitcoin ATM, generated with Midjourney. The tragic irony here being that it took a lot of little old ladies getting scammed to turn the GPU market into what it is today. The moral of this story is that crime does pay, as long as you're the one selling ammunition. Have a good weekend!

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AI isn't just predicting anymore—it's creating. Generative AI has exploded onto the scene, crafting everything from code to images with uncanny human-like ability. As transformer models and multimodal systems push boundaries, we're seeing unprecedented automation potential across industries. But with great power comes great responsibility. The future of work and creativity is being rewritten. How will you adapt and innovate in this new AI-powered landscape? #GenerativeAI #FutureOfWork #AIEthics #TechInnovation #DigitalTransformation What's your take on the generative AI revolution? Share your thoughts below.

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Big news from Meta: llama3.2 is here along with LlamaStack making development of AI systems on edge systems move accessible. This will change the way we use and access open-source AI since the 1B and/or 3B parameter models don't need large amounts of compute. But what about the 11B and 90B LLM models!? Well..... "... Llama 3.2 11B and 90B can’t be accessed in Europe. As a result, several Meta AI features available elsewhere, like image analysis, are disabled for European users. Meta once again blamed the “unpredictable” nature of the bloc’s regulatory environment." I'm looking at you European Parliament and European Commission #ai #aiineurope #tech #llms

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🤖 The future of AI isn't about staring at screens—it's about living in intelligent environments. In my latest piece "The Symbiotic Future: Human-AI Integration in Spatial Computing," I explore how spatial AI will fundamentally transform our relationship with technology. Drawing from theories of extended cognition and environmental intelligence, I argue that we're moving beyond mere human-computer interaction toward true human-AI symbiosis. Key insights: —AI is evolving from tools we use to environments we inhabit —Intelligence will become distributed across our physical spaces —The future is not screen-based but world-embedded —Human and machine intelligence will form recursive feedback loops —This isn't just about better technology: it's about a new chapter in human evolution. Read the full article to discover how spatial computing might reshape what it means to be human in an AI-enabled world. #AI #SpatialComputing #FutureOfTech #Innovation #HumanAI #CognitiveScience #EmergingTech Thoughts? 🤔

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NVIDIA is putting the "silicon" back in "Silicon Valley." It has just become the most valuable company in the world. The stock is up almost 10x since the end of 2022. But if there's one thing you can count on in this world, it's that what goes up fast can come down just as fast. Don't get me wrong, Jensen deserves his Taylor Swift moment. The NVIDIA story is basically business legend. It's a story of perseverance, grit, ingenuity, and "anything's possible if you put your mind to it." And if you get really lucky. And there's good fundamentals behind the stock movement. Its latest quarterly earnings shows a net income of $15B, which is an annual run-rate of $60B, up 7x YoY. Given its growth rate, being valued at 50x annualized net income is almost a modest price to pay. Compared with meme stocks like GameStop, anyway. But the biggest difference between NVIDIA and Apple / Microsoft (which have traded the title of most valuable company between themselves over the last few years) is that Apple & Microsoft have built an incredibly sticky product that sits on top of the value stack. Their ecosystems are massively valuable, making switching away from them in the short term almost impossible. NVIDIA, on the other hand, has a big customer concentration problem. Roughly half of its revenues in recent quarters have come from Amazon Web Services and Microsoft, which have been installing GPUs in their data centers at a feverish pace to meet customer demand for AI workflows. Worse, consumers and the broader economy don't interface with NVIDIA at all, making developers' task of switching away from NVIDIA GPUs that much easier if better / cheaper / faster alternatives were to come along. Remember "Intel Inside"? They used to be the only way to go. But Intel's revenues have dropped 32% from 2021 to 2023 and that trend looks increasingly difficult to reverse. Finally, AI continues to be a massive investment that, so far, has generated little return. If companies decide to take a breather on their AI investment, that can mean a quick drop for NVIDIA's revenue. Of course, the opposite could be true. NVIDIA could continue to dominate the AI compute market. AI investment could continue its meteoric rise. NVIDIA's push into software and cloud services could solidify its position and increase the cost to switch. But whether the "NVIDIA AI Enterprise" (that's a mouthful) is gonna be successful is too early to tell, and certainly will face tons of competition in its fight to the top. Anyway, none of this is investment advice and is for informational and entertainment purposes only. 🙂 #NVIDIA

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AI's memory is sharper than we thought. New research reveals generative AI can recreate images after seeing just 200 copies. This finding raises intriguing questions about AI's learning capabilities and the implications for copyright and privacy in the digital age. What safeguards should we implement to protect intellectual property in an AI-driven world? #AIEthics #CopyrightLaw #GenerativeAI #TechInnovation #DigitalPrivacy

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Loved bringing together a group of research-centric, product-minded technologists building the future of AI tonight in the 🅱️🍎, incl. product / eng leadership @ NVIDIA, Pinecone, Datadog; founding eng @ Abnormal Security, Modal, Counsel Health; applied AI @ OpenAI, Anthropic; research eng @ Meta (FAIR), Harvey, Google DeepMind; founders @ Sapien and some of NYC's greatest stealth AI co's ☄ We covered a lot of ground over 4 hours - some of the recurring themes in our conversations: - Agents:🕴Model inference is getting so much faster, which will unlock AI agents' potential. That said, agents should be trained to handle very narrow tasks, reliably, first vs. an open-ended approach many startups are attempting today - Robotics: 🤖 While the science is not there yet, the robotics market and its impact will be much bigger than LLM. The introduction of humanoids will fundamentally change how we live. That said, the U.S. is in a vulnerable position due to lack of supply chain independence, compared to rivals like China - Value creation: ✨ AI personalization is overrated as consumers mostly care about status (i.e., ‘whatever is the best’) vs. what's tailored to them. Delivering great UX is still hugely undervalued, for both enterprise and consumer use cases. Cost and reliability remain enterprise buyers' front-and-center priorities. AI can preserve endangered rare languages by documenting and creating digital archives / databases cc: our amazing sponsor Arc (Brendan Bettencourt, Erika Bricky, Eric Lo), Visible Ventures

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Meta has revealed five new AI models and research initiatives that aim to enhance AI capabilities across various domains. The company's Fundamental AI Research team has introduced 'Chameleon,' a family of multi-modal models capable of understanding and generating text and images simultaneously, addressing the limitations of large unimodal language models. They have also developed pretrained models for code completion using 'multi-token prediction' to expedite language model training. Additionally, the 'JASCO' model can generate music from text inputs, offering greater control with the ability to include chords and beats. 'AudioSeal' has been launched to detect AI-generated speech and identify AI-produced segments within audio clips, a necessary tool for preventing misuse of generative AI. Furthermore, Meta is addressing diversity in text-to-image models to rectify geographic and cultural biases by releasing automatic indicators and annotations that promote better representation in AI-generated images. By sharing this research publicly, Meta aims to collaborate with the global community and foster innovation in AI responsibly.

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An interesting alternative emerges to transformer-based architectures, and here comes a new acronym - the LFMs...MIT spinoff Liquid debuts non-transformer AI models and they’re already state-of-the-art https://bit.ly/3TQdvnO #govtech #AI #genAI

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Stoked to compare + contrast Liquid NNs, with RNNs + Transformers to see exerts the most influence on performance: Input dimensionality vs. network depth I'm going to prototype two concurrent SLMs using LT-CNN architectures (one prioritizing higher input node count, the other leveraging increased hidden layer depth) to empirically assess the impact.

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Anthropic just released its new multimodal AI model: Claude 3.5 Sonnet. The benchmarks sure need a refresh as AI models keep improving at breakneck speed. But more importantly, each benchmark represents a real-world application, so it's crucial to steer clear of thin wrappers over any benchmarked capability. #claude #anthropic #chatgpt #gpt #openai

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