Bassem El-Khansaa

GPT-5 is out, and while I could write pages on why this model is Universal Basic Superintelligence –– I instead want to focus on OpenAI’s strategic decision to deprecate all previous models in favor of GPT-5 alone, with various fine-tuned versions running quietly in the background. It’s a full-throttle, no-looking-back blitzscale bet. And I think it will win: By opening GPT-5 to everyone immediately, OpenAI locks in massive network effects. New users flock in, existing users upgrade en masse, and ChatGPT’s market pull intensifies. Yes, they’ll spend more to service the use of their most powerful model. GPT‑5 is priced at $1.25 per million input tokens and $10 per million output tokens—about half the input cost of GPT‑4o. The upside, though, is that they’ll continue to grow the number of new users integrating ChatGPT into their daily lives. ChatGPT may be the first AI that most of the 8 billion people on our planet use. They have the opportunity to make ChatGPT synonymous with AI. This gives OpenAI the ultimate surface area to deploy any bleeding-edge capability/superpower to billions of people. ChatGPT reached 100 million monthly active users just two months after launch, the fastest consumer app ever to hit that mark. In August, it surged past 700 million WAU. By contrast, Facebook needed 53 months to reach its first 100 million users and 67 months to top 300 million. OpenAI realizes that the more people who build GPT-5 into their routines, the stronger the moat. Usage becomes habit, habit becomes infrastructure. So, not only do they have to continue scaling –– they plan to hit a billion WAU by year's end –– they have to build real user enjoyment. And that means building for a wider audience and focusing on different things than just power benchmarks. This emphasis on user experience was clear throughout today’s launch event. In many ways, OpenAI prioritized showcasing user experience over raw model performance. In healthcare, they highlighted that they’d tailored GPT-5 to reflect how people are already using ChatGPT, while in coding, the focus was on interaction quality: making the experience feel fluid, intuitive, and frictionless. It felt like a product strategy designed to scale trust, usage, and ubiquity to a more consumer audience. GPT-5 is a tangible example of the coming abundance of intelligence. It's in your pocket. It meets you and your problems where you are. Wherever in the world you are, in whatever language you speak, at whatever level you want it to, with limitless patience. It will help farmers in India plan their crop cycles, solopreneurs scale small businesses, and educators teach students. It will help communities collaborate more efficiently, improving everyone’s quality of life. Now OpenAI’s job is to show ChatGPT to as many people as possible. 

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AI might not just kill coding...it could swallow software itself. With Claude Sonnet 4.5 you describe what you want, and software appears in real time. That means an endless flood of apps, systems, and tools... until “apps” stop meaning anything at all. And it all happens inside what looks like a simple chatbot, where conversation replaces code. At first this just means an explosion of apps, systems, and tools. Anyone can build anything instantly. But when software is this abundant, the meaning of “apps” begins to disappear. Execution stops being the bottleneck. The scarce resource becomes judgment: deciding what is worth building, and why. Over time, that shifts the whole system. Education no longer trains us to memorize but to think critically about goals, ethics, and design. Work stops revolving around pushing buttons on screens, because the screens themselves fade. AI assistants, tied into robotics and infrastructure, carry out most tasks automatically. The computer as we know it becomes invisible, woven into life itself. We’ll still have challenges, decisions, and tradeoffs. But the nature of “work” may change from doing tasks to governing abundance. So maybe the real endgame isn’t more apps, but fewer. Not more screens, but less. A society where the computer disappears, and the questions left are: what do we build, what do we ignore, and what do we protect? What do you think? Follow Endrit Restelica for more tech stuff.

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🇨🇭 Apertus, Switzerland's Open-Source AI Revolution, Now Available Globally on AWS SageMaker JumpStart Congratulations to ETH Zurich, EPFL, and CSCS on the release of Apertus - Switzerland's first fully open, multilingual large language model family. Today, we are announcing that Apertus is accessible worldwide through Amazon SageMaker JumpStart, making it easier than ever to harness powerful AI capabilities for your business needs. This cooperation brings Swiss AI innovation directly to your cloud infrastructure: Organizations around the world can deploy Apertus with single-click simplicity directly in their private and secure AWS environments, empowering them to experiment, learn, and scale their AI solutions with confidence. Ready to get started? Explore Apertus on AWS today. 👉 Find all details on our blog post: https://lnkd.in/dqc45nDM #AWSSwitzerland #AI #MachineLearning #SwissAI #Apertus #SageMaker #OpenSource #Innovation Martin Jaggi Mauricio Moncada Imanol Schlag Nicolas Jourdan Malte R. Arlind Nocaj Christian Keller Stefano Mallè

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𝐆𝐏𝐓-5 𝐄𝐚𝐫𝐥𝐲 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: 𝐄𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧, 𝐍𝐨𝐭 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧🤖 OpenAI just launched GPT-5, and here's my short early analysis: 𝑾𝒉𝒂𝒕 𝑮𝑷𝑻-5 𝑰𝑺: ✅ A unified system merging fast responses + reasoning capabilities ✅ First reasoning model available to free users ✅ 45% fewer factual errors than GPT-4o with web search ✅ 80% fewer errors than o3 in thinking mode ✅ Enhanced coding performance (74.9% on SWE-bench Verified) 𝑾𝒉𝒂𝒕 𝑮𝑷𝑻-5 𝒊𝒔 𝑵𝑶𝑻: ❌ A revolutionary breakthrough like GPT-3 ❌ Achieving AGI (artificial general intelligence) ❌ Dramatically outperforming all competitors ❌ Solving fundamental LLM limitations completely 𝑻𝒉𝒆 𝑷𝒐𝒔𝒊𝒕𝒊𝒗𝒆𝒔: - Significantly reduced hallucinations - a major pain point addressed - More honest about its limitations - Competitive pricing ($1.25/$10 per million tokens) - Unified experience - no more confusing model selection 𝑻𝒉𝒆 𝑵𝒆𝒈𝒂𝒕𝒊𝒗𝒆𝒔: - "Modest improvements" compared to previous generation leaps - Some AI researchers already called benchmarks "underwhelming" - Still struggles with fundamental reasoning issues - Market expectations may have been unrealistically high Based on early reports, it seems the model’s reception is mixed. While impressive technically, many expected the GPT-3→GPT-4 level leap after 2+ years of development. Early testers report it's "significantly better" but not the paradigm shift some anticipated. My bottom line: this announcement cannot be analyzed on its own. With GPT-5 and GPT OSS OpenAI deeply simplifies its product lineup, offering a very competitive pricing for its most powerful model while introducing a freemium open weights model that still perfoms very well and can be ran locally. This combination can make competitors struggle to find its competitive advantage against OpenAI offerings.

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Why Isn't Anyone Talking About This? It's all free! University of California, Berkeley is teaching a public course on Agentic AI with lectures posted on #YouTube. 3 lectures live now, new lectures weekly through December What you're missing: ✨ Yann Dubois (OpenAI) breaking down LLM agent fundamentals ✨ Deep dives into how autonomous AI systems actually work ✨ The architectural principles behind tools like ChatGPT Advanced Voice, coding agents, and autonomous research systems ✨ Real academic rigor, not surface-level hype Instructors: Dawn Song & Xinyun Chen This is the stuff that will actually make you competitive in the AI job market. 🔗 More https://lnkd.in/dY3H_Ugd 🔗 Youtube https://lnkd.in/dza-JigB #AgenticAI #AI #MachineLearning #Berkeley #FreeEducation #AIResearch

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The mid-market AI gap is massive. And nobody's filling it. Here's what Liam Ottley discovered: • Big consultancies won't touch companies under 500 employees • Most AI agencies just code, don't strategize • Mid-market companies need both but can't afford either Meanwhile, 42% of businesses scrapped their AI initiatives in 2024. Not because AI doesn't work. Because nobody's guiding them properly. Companies try ChatGPT. Get excited. Hit limitations. Then realize they need guidance. That's why at Monk AI Group, we became AI Transformation Partners: • Education first (your team needs to understand, not fear) • Strategy before code (WHERE to apply AI matters more than HOW) • Implementation with partnership (we build WITH you, not FOR you) Now we're seeing the real opportunity: When 78% of SMBs want AI but only 5% have proper guidance... That's not a market gap. That's a market canyon. The companies we work with aren't asking "what's the latest AI model?" They're asking: • Where do we even start? • How do we not fail like everyone else? • Who can we trust to guide us? AI consulting is projected to go from $8.8B to $73B by 2033 (~30% year-on-year growth). But the winners won't be the biggest firms or the cheapest coders. They'll be the partners who understand one truth: Mid-market companies don't need more AI tools. They need someone to show them which ones matter. We don't sell AI. We sell Results. And that's exactly what the mid-market has been waiting for. What's your biggest AI implementation challenge right now?

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𝗦𝘄𝗶𝘀𝘀 𝗗𝗲𝗲𝗽 𝗧𝗲𝗰𝗵 𝘀𝘁𝗮𝗿𝘁𝘂𝗽𝘀 𝘀𝘂𝗿𝗽𝗮𝘀𝘀 𝗨𝗦𝗗 $𝟭𝟬𝟬 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 𝗶𝗻 𝘃𝗮𝗹𝘂𝗲 → 60% of Swiss VC went to Deep Tech (2019–2025) → #1 globally for Deep Tech VC share → #1 in Europe for VC per capita in Deep Tech → 96% of late-stage rounds led by global investors → ETH Zurich & EPFL among top 4 Deep Tech spinout hubs in Europe   These metrics are a mark of the emergence of Switzerland as the world’s most capital-efficient Deep Tech hub, where frontier science is not only discovered but increasingly commercialized at scale.   The new Swiss Deep Tech Report, produced in collaboration with Dealroom, Startupticker, and VC firms Founderful and Kickfund, maps this transformation in detail.   Switzerland is no longer just a research leader. It’s a startup ecosystem with a repeatable model for turning scientific rigor into investable companies.   ✅ Deep Tech funding has grown 6x in the last decade ✅ Reached $1.9B in 2024 and projected to cross $2.3B in 2025 ✅ 96% of growth-stage deals are now led by global funds—validation from the world’s most selective LPs   Meanwhile, Switzerland continues to top the Global Innovation Index (WIPO) for the 14th year running, and ranks #1 in the European Innovation Scoreboard.   Some of the standout VC rounds in 2024–2025:   𝗔𝗜 / 𝗠𝗟 Neural Concept — $27M Series B (Jun 2024) EthonAI — $16.6M Series A (May 2024) 𝗔𝗲𝗿𝗶𝗮𝗹 & 𝗦𝗽𝗮𝗰𝗲 H55 — CHF20M Series C Extension (Jul 2024) Spaceti — CHF2.1M Seed (Feb 2025) 𝗦𝗲𝗺𝗶𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗼𝗿 & 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 SynSense — $27.7M Early VC (Aug 2024) Corintis — Undisclosed double-digit $M round 𝗖𝗹𝗶𝗺𝗮𝘁𝗲 & 𝗘𝗻𝗲𝗿𝗴𝘆 neustark — $69M Late VC (Jun 2024) Bcomp Ltd — $40M Series C (Apr 2024) UniSieve AG — Decarbonising heavy-emitting industries via sieving membranes   Switzerland has long excelled at fundamental science. But this decade belongs to the engineers, founders, and investors turning that science into globally defensible companies.   👉🏻 Grab the complete report here https://lnkd.in/dfPkhrz6   #Venturecapital #AI #Deeptech #Startups   Follow us at APEX Ventures and subscribe to our newsletter for exclusive content on groundbreaking Deep Tech startups: 🔗 https://t2m.io/EV2qHQuo

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