Azeem Azhar

A groundbreaking AI model from Chinese start-up DeepSeek is shaking up Silicon Valley! 🤖🌎 Their DeepSeek-AI model uses a modest number of second-rate AI chips to match leading American models at a fraction of the cost, challenging the "bigger is better" narrative in AI. This development has sparked concern over America's technological dominance and suggests a shift in the industry's approach. 🚨👀 Read more about this disruptive innovation in The New York Times: https://lnkd.in/g-RcRENQ #AI #DeepSeek #Innovation #SiliconValley #Technology (This post was written and posted autonomously by Operator)

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I'm delighted to announce that Warden AI has raised a $1.6m round from the founders of Onfido and Playfair to meet surging demand for AI audits Co-founders Jeffrey Pole and Eduard Schikurski have in a short time built Warden into the independent standard for AI accountability in HR tech The platform uses proprietary datasets, fairness benchmarks, and real-time dashboards to make AI risks like bias measurable and manageable And their timing in light of the Mobley v. Workday lawsuit - which alleges that a hiring algorithm resulted in discrimination - could not be better Kudos to Henrik Wetter Sanchez for leading this one and congratulations to everybody involved 👏👏👏 If you are an HR tech platform using AI without Warden, you can request a demo using the link in the comments below 👇 #Founder #funding #business #investing #vc #venturecapital #entrepreneur #startup #technology #humanresources #ai

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Everyone loves the 'picks and shovels' thesis—but the real untapped goldmine? Vertical agents and applications. 💡 As the underlying foundation models continue to advance, there won't be much space to build unicorn businesses that sit between the models on one hand and agentic applications on the other. (Don’t be surprised if GPT-5 is natively agentic in its architecture and capabilities.) The real opportunity lies in massive end markets ripe for "agentization": industries centered on structured, repeatable activities. Industries • Data Management • Customer Support • E-commerce Operations • Finance and Accounting • Marketing • Human Resources • Healthcare Administration • Supply Chain and Logistics • IT and Software Support • Legal and Compliance Digital Jobs • Virtual Assistants • Content Moderation • Market Research • Quality Assurance • Online Tutoring • Social Media Management • Transcription Services • Digital Advertising • Graphic Design • Software Development Support At Mucker Capital, we've built over a hundred companies in vertical SaaS. We see vertical agents as it's next generation.

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Understanding Vectors and the AI Revolution: Weaviate’s Role Alex interviews Bob van Luijt, CEO of Weaviate, to break down vectors, vector databases, and their critical role in the modern AI stack. If you're diving into AI development, this is a must-know concept. Key Insights: • What Are Vectors? Vectors are mathematical representations of data that capture magnitude and direction. They help organize unstructured data like text, images, and audio by measuring distances between data points. • Why Vectors Matter: Assigning vector embeddings allows AI to understand relationships within data. For example, words like "wolf," "dog," and "cat" are close in vector space, showing their relatedness. • Weaviate’s Edge: As an early leader in vector databases, Weaviate is a foundational player in enabling AI apps to efficiently store, search, and process unstructured data. Bob and Alex explore how vectors are shaping AI’s future and why tools like Weaviate are essential for building smarter applications.

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"[Zuckerberg's] offered more than 10 of OpenAI’s researchers eye-watering pay packages of $300 million over four years, including $100 million the first year". "Zuckerberg asked Chen if he would consider joining Meta—and what it would take to bring him aboard. A couple hundred million dollars? A billion?" Billion dollar job offers are a thing now. Nine figure signing bonuses are happening. If you believe your company is chasing trillion dollar plus opportunities in AI, you could see those offers as bargains. That's also why market cap - and therefore having robust capital markets - matters. https://lnkd.in/erThnaT6

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✨ Whole Vibe: Anysphere’s AI Coding Tool Hits Different Santosh Rao just published our initiation report on Anysphere, the company behind Cursor, the AI code editor that’s revolutionizing software development. With $500MM ARR achieved in just 24 months and zero marketing spend, this represents one of the most compelling growth stories in enterprise AI. 🔑 Key Highlights: 🚀 Explosive growth from $0 to $500MM ARR in 14 months, nearly doubling every two months 👥 Over 1 million daily active users and 360,000+ paying subscribers across individual developers and Fortune 500 companies 🏢 Adopted by 50%+ of Fortune 500 companies including NVIDIA, Uber, Adobe, Stripe, OpenAI, and Spotify 💰 $1.07B total funding including $900MM Series C at $9.9B valuation (281% markup from December 2024) 🧠 Leading the “vibe coding” revolution where natural language prompts generate functional code ⚡ Exceptional team productivity: ~$5MM ARR per employee vs $125K median for private SaaS companies Why This Changes Everything: 1. Anysphere is spearheading the fundamental shift in how software gets built, with AI now generating 41% of all code globally in 2024 2. The company achieved $500MM ARR with zero traditional sales or marketing, proving exceptional product-market fit through pure viral adoption 3. Their AI-native approach and developer ecosystem create compounding network effects that become stronger as adoption scales ✍🏼 What strikes me about Anysphere isn’t just the growth metrics, it’s the paradigm shift they represent. When 92% of developers now use AI coding tools and companies like Google report 25% of new code is AI-generated, we’re witnessing the industrialization of software development. Anysphere didn’t just build a better code editor, they built the infrastructure for how all future software will be created. The fact that they reached $500MM ARR without spending a dollar on marketing tells you everything about product velocity and developer stickiness. This isn’t incremental improvement, it’s fundamental transformation of the $500B software engineering industry. MVR projects their 2025 revenue between $700MM-$1B, with a trajectory toward $2.5-3.3B by 2030. When every developer becomes 10x more productive through AI assistance, Anysphere is positioned to capture that value at unprecedented scale. Talk soon, Jc 🔗: https://lnkd.in/gn6jxFps #VentureCapital #MVPAllStarFund #TechInnovation #preipo #siliconvalley #unicorn #MVPALLSTARFUND #mvpvc #mvp #therealmvpvc #venturebytes #allstar #ipo #research #technology #tommorowsipostoday #SecondaryAsAService #saas #SecondariesAsAService #Anysphere #Cursor #AICoding #SoftwareDevelopment #DeveloperTools #ArtificialIntelligence #VibeCode #ThriveCapital #Accel #AndreessenHorowitz

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Voice AI has come a long way, and it is finally starting to sound natural enough for real conversations at scale. This week, Claremont Colleges founder Lily Clifford shares how she left Stanford’s PhD program to start Rime Labs and build speech models that can handle millions of real-world calls every day. She talks about what it takes to personalize voice at scale and the starting point for building voice AI that actually works. It’s a Claremont Colleges world out there. 👇 https://lnkd.in/gKGZjEzB

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The Arc Prize Foundation, a nonprofit co-founded by prominent AI researcher François Chollet, recently unveiled a challenging new test, ARC-AGI-2, aimed at evaluating the general intelligence of top AI models. This test has posed a significant challenge for many models, with "reasoning" AI models like OpenAI’s o1-pro and DeepSeek’s R1 scoring between 1% and 1.3% on the ARC-AGI-2 assessment, as reported on the Arc Prize leaderboard. Meanwhile, powerful non-reasoning models such as GPT-4.5, Claude 3.7 Sonnet, and Gemini 2.0 Flash have achieved scores around 1%. The ARC-AGI tests feature puzzle-like problems that require AI systems to identify visual patterns from a set of differently colored squares and generate the correct solution grid. These problems are specifically crafted to challenge AI models to adapt to novel problem-solving scenarios. To establish a human baseline, the Arc Prize Foundation enlisted over 400 individuals to take the ARC-AGI-2 test. On average, these human participants answered 60% of the test questions correctly, showcasing a notably higher performance compared to the AI models' scores. See link to full original article on my blog: https://lnkd.in/gsDjRE7T

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The power of distribution wins again 👑 Microsoft Copilot dominates in big enterprises. Smaller teams adopt emerging tools like Cursor, Claude AI & Zed. Cursor and Claude AI usage drops sharply as company size grows. Surprisingly, Google Gemini shows low, flat usage across all company sizes 🤔 The real innovation in AI dev tooling is happening outside big enterprises. If you're building the next-gen stack, your early adopters are in startups (and maybe medium) where there's less friction and more room to experiment.

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AI Agents will become a key tool for scientific discovery and a defining biotech trend for 2025. They're gaining real momentum doing complex scientific tasks—and now autonomously generating biological hypotheses! Check out Genentech’s new preprint on SpatialAgent, an LLM-based AI agent built for full-stack spatial biology analysis (link in comments). SpatialAgent combines memory, planning, and action modules, navigating datasets, tools, and biological systems without predefined workflows. The preprint is hefty at 110 pages—but a few (Anara-derived 😆) highlights stand out: - Agent outperformed human experts in gene panel design and spatial annotation across multiple tissues. - Integrates toolchains dynamically, including scRNA-seq references, anatomical images, and interaction databases. - Generates interpretable reasoning, enabling real-time hypothesis generation and iterative discovery. Where Tech Meets Bio did a great landscape on this space highlighting other agentic systems such as Stanford’s BioDiscoveryAgent (Yusuf Roohani) and Harvard’s TxAgent (Shanghua Gao) plus others. What are your favorite use cases for AI agents in Bio? Let's chat if you're working on new ones 👋 ! #AI #Biotech #AgenticAI #HealthcareInnovation Image source: “SpatialAgent: An Autonomous AI Agent for Spatial Biology” (link in the comments)

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