Tuoc Luong

AI memory is fundamental for conversational AI and AI agents. It is critical for building personalized experiences and improving reasoning. Check out Letta’s course to understand how to use AI memory to enhance the customization and quality of your AI app.

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💡 Why do we need so many evaluation tools for LLMs? As engineers, we build 'production-ready' LLM products using these metrics. But what happens next? How do we maintain control and ensure reliability? At Feedback Intelligence, we’ve crafted a cookbook to keep your LLMs reliable and aligned with user expectations. 🍲 📖 Give it a read and let’s chat!

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📈 AI Startup Sierra Expands HQ in San Francisco (4K to 41K SF) 🌁 Artificial intelligence firm Sierra is making a bold move by relocating to a larger office within San Francisco. The startup has signed a lease for a 41,104-square-foot space at 235 Second St., significantly upsizing from its current 4,000-square-foot office. 🏢 This move to San Francisco's South of Market neighborhood, where office vacancy rates have started to decline for the first time since 2020, is a positive sign for the city's hard-hit office market. The area's office vacancy rate, though still high at 28.8%, is slightly lower than six months ago. 📉 The deal contributes to the increase in leasing activity in San Francisco, which is up by about 1 million square feet compared to last year. This uptick is driven by the region's reputation as a leading national hub for AI companies. 💼 Sierra joins other AI firms expanding in the South of Market area, including Scale AI, which signed the city's largest office lease of 2024 with a 178,000-square-foot deal. So far this year, office tenants have signed leases totaling 750,000 square feet in South of Market, a significant increase from last year's 370,000 square feet. 🚀 Co-founded in 2023 by former Salesforce CEO Bret Taylor and former Google executive Clay Bavor, Sierra raised $85 million earlier this year to develop a customer support AI tool for businesses. The firm is set to relocate from its current space at 215 Second St. by next month. San Francisco's reputation as an AI hub, bolstered by its talent pool and six major AI research institutions, continues to attract companies. Recent significant deals include OpenAI’s sublease of over 400,000 square feet of Uber’s former headquarters and Anthropic’s takeover of Slack's former headquarters. These developments reflect a resilient and adaptive real estate market. As a commercial real estate professional, I’m excited to see how these trends shape the future of office space in our vibrant city.

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🧩 One thing we've noticed with #VentureIQ technology is how well it can distill and communicate complex technical material 🧩 Whether it's a #deeptech venture, a novel #AI application, or even a patent submission, we can quickly distill the business and strategic implications for investors...and sometimes even the founders/PIs themselves! 🤯 Based on our work so far, the tech can handle a wide array of research areas and technological sectors -- anything from blockchain algorithms to vaccine development. It handles the nuance of the field, the specific terminology, and extracts the key concepts which matter for venture-building. 🤓 To demonstrate, I took a patent I helped write with Eric Laber on reinforcement learning. I ran it through #Ventureiq to build a commercial assessment (key differentiators, target markets). Then for fun I had #NotebookLM make a podcast out of it. I've uploaded the result it here (DM me if you'd like the actual report): https://lnkd.in/eiTejsny This is more than just automation or streamlining operations - it's about unlocking clarity and insight when it was previously unattainable, and the ability to do it over and over again no matter the sector or vertical. Interested in more info? DM me so we can chat.

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Was chatting with another investor today on a call, and mentioned Tim Urban's Wait But Why Blog post, "The AI Revolution" and how prescient it was. Given that it was written in 2015, decided to flex AI's latest muscles to give it a new venue: a podcast. Podcast here: https://lnkd.in/gW8Dh89U Pretty easy to do: Step 1: Save the posts as PDFs. Step 2: Upload to NotebookLM, have it create a podcast. Step 3: Upload to Descript, give it captions. Step 4: Export, publish to Youtube. Total time to create the podcast: ~25 minutes. To generate this podcast and publish it even a few years ago would have taken >8 hours. Love the future (Original posts: https://lnkd.in/gW-PQXE7, https://lnkd.in/gg-nRvxz) #AIRevolution #GenerativeAI #WaitButWhy #TimUrban #NotebookLM #AIContentCreation #Podcasting #Descript #ArtificialIntelligence #ContentFlex #ProductivityHacks #FutureOfAI #AIinMinutes #TechEfficiency #AIandCreativity #YouTubePodcast #InnovationInContent #vibecap #vibecapital

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Language is powerful--but the first way we interact with and learn about the physical world is through spatial intelligence. Building AI capabilities that enable us to perceive, reason and create in a truly 3D world requires a team that is out of this world. Enter World Labs. Martin Casado and I are thrilled to partner with the brilliant and tireless Fei-Fei Li, Justin Johnson, Christoph Lassner and Ben Mildenhall as they expand the aperture of AI to real and virtual 3D worlds. We've only scratched the surface of what's possible with AI. The chance to back the pioneers of ImageNet, NeRF, Style Transfer, and Gaussian Splats while they tackle spatial intelligence to create generative worlds is why I joined Andreessen Horowitz.

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I like this idea of "technical taste". It gets into where software engineering is as much creative art as it is science. Four great takeaways (IMHO) for software devs in this era in particular: 1. Aspiring engineers should cultivate a sense of curiosity, experiment with different tools and technologies, and embrace a mindset of continuous learning. 2. AI has the potential to streamline processes and enhance productivity for engineers, but it may also lead to disruptions in traditional software development workflows. 3. Developing technical taste and judgment is essential for making informed decisions about which technologies and approaches to pursue. 4. Collaboration and open-mindedness are key to leveraging the full potential of AI and staying ahead of technological advancements. I also really liked these two quotes from Sam Schillace: 1. "The right time to do something is when you have that feeling in the pit of your stomach that's like, 'oh, this is a great idea and it's going to suck to build because nothing's ready yet.'" 2. "Technical taste is like, 'how well have you consolidated that set of experiences and heuristics into judgment that you can apply accurately when you see new things?'" 3. "It may be the case that very small teams can do very large projects, or like we were talking about before, it may be the case we're just going to get really ambitious about what we try to do with the same size of teams, which is kind of where I would put my money." Great job on continuing to put out great episodes, Brett Berson and team First Round Capital! #ai #engineering #softwaredevelopment

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You down with MCP? Who’s down with MCP? Just came across the Model Context Protocol (MCP) from Anthropic. 😎 Think of it as OAuth for AI agents, defining and controlling how they access tools and data. Or maybe a new syslog for AI agents, logging every interaction for auditing and anomaly detection. Either way, feels like the start of something important in security. Here’s why I’m paying attention: 1️⃣ Momentum: Anthropic not only created MCP, but they’re spending big resources to define how “Agentic architectures” should work. 2️⃣ Structure: MCP gives us a framework to monitor and audit AI interactions, a critical need as these systems scale. 3️⃣ Transparency: By focusing on data connectivity, permissions, and access control, MCP could open the door to the next gen of AI security tools. 4️⃣ Consistency: Predictability matters in security, and MCP’s structured approach could make it easier to validate and trust these systems. What could people actually do with MCP? I dunno, maybe build an AI monitoring product, audit agents for compliance, use it to change permissions, see the data they're accessing, log activity for misuse, etc. It feels like one of those early signals of a new "inspection point", like eBPF for containers. Anyone in cybersecurity focusing on this layer?! https://lnkd.in/ey3X9eVV https://lnkd.in/e-82jcWy #cybersecurity #AI

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Intersection of AI and humanoid robotics presents one of the biggest opportunities for societal scale impact Perception, Sensors, and LLMs are merging. Looking out for break out ventures working at this intersection. ! #EmbodiedAI https://lnkd.in/emK-nVNx

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We just concluded Embiggen X’s strategy for 2025. For almost two years, we’ve experienced conversations and priorities shift for large companies - more focus on innovating the core the business and less on non-core innovation initiatives. We’ve seen large global companies in the west close down their innovation labs, corporate venturing units, and let go of non-core innovation teams — or at the very least, decreased spending in venturing activities. This is also true for large corporates in Southeast Asia. Simultaneously, we’ve been getting into conversations with CEO’s asking more questions on AI & Digital Business Transformation. No, I’m not talking about building apps. We’re getting questions around: - How do we rewire the “guts” of our operations for us to be able to “scale profitably”? - How do we fix our “spaghetti & siloed” operations? - How do we make sure that we don’t just “buy more” off-the-shelf tech platforms that don’t talk to each other and complicating our already inefficient ops? - How do we increase our NPS score by transforming our customer experience? - Can you help us build a holistic digital business transformation strategy and help us execute too? - How and where can we use AI to become grow better? This is why Q4 of last year in the midst of business challenges, we decided to shift focus from Corporate Venture Building and spin off an AI & Digital Business Transformation company, Embiggen X (https://lnkd.in/geVM4BCF), from the Embiggen Group. Within less than a year, we’ve expanded our operations in Southeast Asia to Europe and 2024 as our highest revenue & profit generating year. We’ve served companies from Insurance, Supply Chain, Telco, Conglomerates, Construction, and Consumer Services to date. We help from Strategy to Execution. I’m beyond grateful to the operating team that made this new chapter of our journey possible. Embiggen X Managing Partner & COO, Xavier (X) Marzan; Partner & Head of Europe, Nicolas Souvlakis (calling in from Switzerland); Junior Partner & CAO Bien Herrera; Partner & CTO Robert Newgen; Chief Growth Advisor Gary de Ocampo, GICD; Advisory Board Member and Incoming Board Director Cliff Eala; Head of Artificial Intelligence Miguel Testa (calling in from Canada); as well as more partners, clients, and supporters. Big goals & challenges up ahead. Excited for whats to come. Onwards & upwards. 🚀

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Are LLMs better at Deductive (start with a general formula/relationship and compute outputs for different inputs) or Inductive (start with examples of inputs and outputs and figure out the generalized relationship) reasoning.... The answer is they are better at Inductive reasoning... Based on this what kind of applications are they better suited for???? More details in this amazing study....https://lnkd.in/gjKYUraW

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Game changer? Llama 3.1 405B is now running on Cerebras! – 969 tokens/s, frontier AI now runs at instant speed – 12x faster than GPT-4o, 18x Claude, 12x fastest GPU cloud – 128K context length, 16-bit weights – Industry’s fastest time-to-first token @ 240ms https://lnkd.in/e5zuEnM7

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Our latest AI+DePin update is transforming crypto bit by bit. Now, AI miners on the GPT Protocol network can autonomously spin up VMs, harnessing NVIDIA (or any GPU) power for optimized AI task processes on our grid computing system. With 'llama.cpp' auto-compiled, the execution of open source LLMs (ex. Mistral 7B) is now sharper and more robust than ever. This is perfect for AI researchers. This isn't just progress; it's a paradigm shift. We're pioneering the Internet of AI, reducing costs, and supercharging efficiency. The future is decentralized, and with our AI compute crowdsourcing, we’re not just following trends—we’re setting them, for real. Get ready to experience the democratization of AI and blockchain like never before. ⚡️🤖 #AI #DePin #DecentralizedAI $GPT

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AI that can use computers like humans? Anthropic just made it a reality. Anthropic's latest announcement is reshaping the AI landscape: 1. Upgraded Claude 3.5 Sonnet with industry-leading software engineering skills 2. New Claude 3.5 Haiku model matching top-tier performance at lower cost and speed 3. Groundbreaking "computer use" capability allowing AI to navigate interfaces like humans 4. Significant improvements in coding, with Claude 3.5 Sonnet outperforming all publicly available models on SWE-bench Verified 5. Early adoption by tech giants for automating complex, multi-step processes This leap forward in AI capabilities opens up exciting possibilities for automation, software development, and open-ended research tasks. However, it also raises important questions about responsible deployment and potential risks. What are your thoughts on the implications of AI systems that can use computers like humans? How might this change the future of work and technology? #ArtificialIntelligence #TechInnovation #FutureOfWork #AIEthics #SoftwareEngineering Share your insights in the comments!

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Attached is NVDA's price chart for the last year - up c.175% (up 2500%+ in L5Y period!!) 🚀 I nonetheless have conviction that it currently remains undervalued... Among other things, due to strong competitive positioning as a GPU-maker, AI-driven demand fuelled by investor and consumer interest, and moats it has built. This is mirrored by equity analysts – GS’ latest price target was $800, BofA’s $1,500. I do believe the growth is capped, and driven in equal measure by under-supply and bubble-like demand as it is by fundamentals. Even so, Nvidia remains an attractive medium term investment. ⚖️ Demand – Supply Dynamics: AI is a generational innovation, and agents /apps are already upending SaaS, or at least so think VCs who deployed $64.6B in AI start-ups in 2023 alone. As early movers and now the industry standard (c.80% market share), Nvidia's A100 and H100 chips are not only the most efficient option, but also crucial for large scale AI training and inference (chips are the biggest cost head for LLM companies). With unprecedented interest in AI (ChatGPT acquired 1M users in 5 days of launch, OpenAI reported $3.4B ARR in Apr’24, AI agents are widely recognised as the tech of the future), Nvidia stands to capture a large portion of the $250-$500B data centre conversion market over the next 5 years​. This is proven by the $22.6B in data centre revenue Nvidia brought in during Q2’24, up 23% from the previous quarter and up 427% from a year ago 🥇Competitive positioning: While Intel, AMD, Arm have been active, the only credible competitor, AMD, has a relatively smaller market share in the high-performance AI GPU segment, and Nvidia’s consistent technological advancements keep it further ahead, e.g., Nvidia’s Rubin which will succeed Blackwell in 2026 is orders of magnitude better than anything on-market. 🤝Moats via ecosystem building: Collaborations with hyperscaler cloud providers like AWS and Microsoft Azure have expanded Nvidia’s reach. Moreover, acquisitions like Mellanox have strengthened its position in high-performance networking, critical to AI infrastructure. Coreweave, a prominent cloud services partner / distribution channel for chip capacity is an NVIDIA investee and is built almost entirely on Nvidia chips. Finally, they continue investing in networking, software tools, data centre solutions but also purpose-built AI PC and smartphones to create an ecosystem that not only locks in customers and enhances switching costs, but pivots more of their revenue to more predictable recurring contracts. 📈 Financial underpinnings: Nvidia’s expected FCF for next 2 years stands at $100B, providing huge ammo for R&D, strategic investments and M&A (only $30 to $35B earmarked for buybacks) and in turn, growth. Even so, their shares trade at a P/E ratio of c.20x  NTM earnings, far below historical median of 35x+, indicating the market expects them to grow in the medium term. KEEN TO HEAR THOUGHTS! #Nvidia #AI #Compute #Chips #Tech #Growth

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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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Why rely on one #foundationalmodel for your #GenerativeAI strategy when you can federate + #innovate across them. Tabnine adds GPTx + Mistral + Anthropic and gets named "Luminary" status by Everest Group. Trusted by millions of developers and thousands of company's - AI you control. I love #investing in #extraordinary #founders!

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