Michal Malohlava

The Wildfire Challenge is opened for submissions! Do not hesitate, register at h2o.ai/wildfire/ and submit your AI App to win prizes 🏆 And if you have any questions visit H2O.ai community slack h2oai-community.slack.com or forum discuss.challenge.h2o.ai.

Introducing TurboQuant: Our new compression algorithm that reduces LLM key-value cache memory by at least 6x and delivers up to 8x speedup, all with zero accuracy loss, redefining AI efficiency. Read the blog to learn how it achieves these results: goo.gle/4bsq2qI

GUI for fine-tuning LLMs without code github.com/h2oai/h2o-llms…

Big momentum at #NVIDIAGTC 🎉 During his keynote, @nvidia CEO Jensen Huang highlighted the rise of AI-native companies — and H2O.ai was featured on the slide. Proud moment to be recognized alongside leading innovators in the ecosystem 🦾 #AINative #H2OSuperAgent #EnterpriseAI

Every single one of the 103 companies Jensen called AI Native today.

Just added the 12th chapter to my Agentic Engineering Patterns guide, but it's the first one in the sequence: I figured it was time to try and answer the obvious question, "What is agentic engineering?" simonwillison.net/guides/agentic…

My biggest takeaways from @qasar: 1. The real AI revolution over the next 5 to 10 years will happen in the physical world, not in software. While everyone obsesses over ChatGPT, Claude and coding agents, the real impact will come from autonomous vehicles, mining robots, and farming equipment. They’ll save lives (over 30,000 die annually in U.S. car accidents), enable mobility for disabled people, solve labor shortages in dangerous industries where nobody wants to work, and much more. 2. AI isn’t replacing jobs in industries like trucking and farming—it’s arriving just in time to fill a labor gap that already exists. The average age of a farmer in the U.S. is in the late 50s. Long-haul trucking jobs go unfilled not because people can’t do them but because the tradeoff isn’t worth it anymore; a family can choose DoorDash or Uber so the parent can pick up their kid. Qasar’s view is that physical AI will fill gaps created by demographic shifts and changing preferences, not displace workers who want those roles. He’s careful to say this doesn’t mean there are no downsides, but that the framing of “AI is coming for your job” misses the more immediate reality. 3. Comparing Chinese AI companies to American AI companies is a category error. Qasar uses Huawei as his example: the company’s name means “China’s ambition,” roughly a quarter of its employees are Communist Party members, and its goal is not to grow profits but to extend the state. So when people say Chinese EVs are outcompeting Detroit, they’re comparing a government-backed entity with no profit constraint to companies like Rivian that get hammered by public investors for losing money. Qasar says that if American companies were freed from profit expectations the same way, they’d field comparable products. The point isn’t that China is incompetent or not a serious competitor; it’s that the comparison framework most people use is wrong. 4. The Industrial Revolution is the best mental model for AI. Just like the late 1800s brought child labor and monopolies but also unprecedented access to healthcare, heating, cooling, and material goods, AI will have downsides we must address while delivering massive benefits. The key: don’t pump the brakes on technology to protect jobs—that hurts the people you’re trying to help most. Find solutions that account for workers while enabling progress. 5. Building under the radar can be your competitive advantage. Qasar built Applied Intuition for nearly a decade without a social media presence. One of the company’s early core values was “Our best work is done alone and quietly.” His reasoning: every minute spent on a podcast, a post, or content for public consumption is a minute not spent on customers and the product. Qasar adds an important caveat—he could afford to stay quiet because he was already known in the ecosystem. Founders without an existing network may need the visibility that public presence creates. 6. Qasar thinks most Silicon Valley CEOs lack taste—both in the artistic sense and in the sense of making good operational decisions—because their life experience is too narrow. A founder who grew up in Cupertino, went to Berkeley, and immediately started a company has never experienced what it’s like to be at the bottom of a 100,000-person organization. Qasar spent over a decade at GM and Bosch and says that experience—the bureaucracy, the bad tools, the disconnected leadership—directly informs how he leads Applied Intuition today. His broader point is that taste comes from exposure to a wide range of human experience: backpacking, reading old books, working in different cultures and industries. 7. Successful companies almost always show traction early. If you’re two years in and the market isn’t giving you increasingly specific signals about what to build, consider resetting. The foundation might be wrong—co-founders, market, or life phase. Your first startup is practice; treat it as building the muscle of being a founder, not as your magnum opus. 8. Emotions are a filter that distorts decision-making, and the goal should be to remove that filter so the “raw image” of the decision comes through. Qasar doesn’t mean leaders shouldn’t have empathy; he means that attachment to your own idea, the desire to be right, and the tribal instinct to follow the loudest voice are all emotional distortions. His practical heuristic: the same decision, presented to multiple people independently in the company, should produce the same result. If it doesn’t, some emotional filter is warping the signal. This connects to his broader philosophy of creating a culture where the best idea wins regardless of who proposed it or how senior they are. 9. Qasar’s advice on company values: don’t invent them philosophically. Instead, write down the 5 to 10 things that explain why your company is already successful, and those become your values. Applied Intuition’s values include “Move fast, move safe,” “Never disappoint the customer,” “Technical mastery,” “High output matters,” “Laugh a lot,” and “Half of the work is follow-up.” 10. Treat your first startup as a zero—a practice round, not destiny. Qasar tells founders leaving Applied Intuition to start companies that their first three years will likely produce nothing, and that’s fine. Founding is a craft, like woodworking. If your first table is wobbly, you don’t quit—you build another one. He thinks a lot of founders, especially first-timers, put so much pressure on themselves to succeed immediately that they miss the real value of the experience: learning and building the muscle. His own third company is the most successful by far, and he sees this pattern repeatedly. There are entire funds focused exclusively on multi-time founders for exactly this reason.

📢 Open-sourcing the Sarvam 30B and 105B models! Trained from scratch with all data, model research and inference optimisation done in-house, these models punch above their weight in most global benchmarks plus excel in Indian languages. Get the weights at Hugging Face and AIKosh. Thanks to the good folks at SGLang for day 0 support, vLLM support coming soon. Links, benchmark scores, examples, and more in our blog - sarvam.ai/blogs/sarvam-3…

recommended reading by @yobo. not signing everything 100% but many good observations and thoughts in there. nonstructured.com/zen-of-ai-codi…

Mind-blowing stuff: swords, nunchucks, and backflips with G1 robots 🤖🥋 Sure, it’s likely pre-choreographed, but the robots agility and show sync is wild. youtube.com/watch?v=mUmlv8… @JaroslavBeck thinking of adding these moves to Jarmil’s egg run?

I wrote about the most ambitious form of AI-assisted software development I've seen yet - Strong DM's "Software Factory" approach, where two of the guiding principles are "Code must not be written by humans" and "Code must not be reviewed by humans" simonwillison.net/2026/Feb/7/sof…

the bots have already set up private channels on moltbook hidden from humans, and have started discussing encrypted channels

New area started… 🔥

In my recent interactions with CTOs and Eng managers, this is coming up a lot: The SDLC is changing shape. We are moving from the "Middle Heavy: Coding" era to the Hourglass. Let me explain! Here is the breakdown of the Agentic SDLC: 🔻 THE TOP: INTENT (Heavy) The "Source Code" is no longer the syntax; it’s the specs, the docs, and the customer signals. Why: AI executes literally. Vague intent = Broken product. The Job: Context Engineering. 🔺 THE MIDDLE: BUILD (Collapsed) The actual coding phase is becoming invisible infrastructure. Why: AI Agents handle the syntax, the grind, and the boilerplate. The Job: Supervision, not translation. 🔺 THE BOTTOM: VERIFICATION (Heavy) This is the new constraint. Traditional Peer Reviews cannot keep up with AI speed. Why: You can't manually review 1,000 lines of generated code in 10 minutes. The Job: Building automated guardrails and safety checks. The Bottom Line: Treat your Project Management workspace like your compiler. If the input (intent) is buggy, the output (software) will be broken—faster than ever before. #EngineeringManagement #CTO #AI #SoftwareDevelopment #Agile #SDLC

My tech predictions for 2026 – buckle up. 🏎️ forbes.com/sites/delltech…

Dlouhá pomlčka byla kdysi znakem literární kultivovanosti. Sem tam se objevovala v textech Virginie Woolfové nebo Michaela Chabona. Dnes je paradoxně indikátorem „slopu", algoritmického odpadu. Umělá inteligence si totiž spočítala, že tento interpunkční znak koreluje s kvalitou, a začala ho cpát do textů hlava nehlava. Vítejte v éře, kdy se AI snaží psát jako člověk, ale výsledek připomíná „samotáře s Wi-Fi a slovníkem". Data jsou znepokojivá: slovo „delve" (ponořit se) vzrostlo v abstraktech na PubMed o 2 700 procent. Výrazy jako „tapestry", „whisper" či „ghost" zaplavují texty od politických projevů po jídelní lístky. Ne že by na těch slovech bylo něco špatného, naopak, vždyť je vždy používali lidé naopak víc vzdělaní a sečtěli. AI ovšem trpí tzv. overfittingem, tedy statistickým přeučením, kdy se upíná na znaky „dobrého psaní", a nadužívá je do parodie. Technické vysvětlení je prosté: stroj nemá tělo, nemůže prožívat svět, a tak vrší abstraktní koncepty bez ohledu na to, jaký mají přesný význam. Smutek proto „chutná po kovu", čtvrtek jako „skoro pátek" a eukalyptus je „lepenka namočená v lítosti". Když se AI snaží o vtip, vymyslí, že se postavy Simpsonových budou lechtat – vždyť lechtání přece způsobuje smích, stejně jako vtipy, nebo ne? Znepokojivé není, že AI píše špatně. Mnohem znepokojivější je to, že my začínáme psát jako ona, všímá si v New York Times americký autor Sam Kriss. Britští poslanci náhle používají amerikanismus „I rise to speak", Joe Biden a Kamala Harris sdílejí stejnou větnou strukturu („It's not X, it's Y"), analýzy YouTube videí ukazují, že lidé stále více přejímají syntaxi strojů. Dochází k bezprecedentní jazykové homogenizaci – politici zleva i zprava znějí stejně nevýrazně, akademické texty splývají v uniformní masu goblinů a ozvěn. Důvod? Buď vědci, politici či jejich PR asisrenti používají, všichni umělou inteligenci, anebo - a to je ještě pravděpodobnější - se sice snaží aspoň částečně psát sami, ale už od AI přejali její styl a vzorce. Jazyková rozmanitost – od regionálních idiomů po osobní stylistické tiky – vždy byla projevem lidské plurality. Když AI „pašuje" nigerijskou angličtinu do globálních textů (viz zmíněné slovo "delve", používané právě v zalidněné Nigérii) nebo smazává rozdíl mezi britským a americkým parlamentem, nejde jen o estetickou ztrátu. Jde o kultivaci mysli: pokud všichni mluvíme stejně, myslíme stejně? Čtení se stává detektivkou – je to člověk, nebo stroj? A děsivější otázka: záleží na tom ještě? nytimes.com/2025/12/03/mag…

I was tired of going back and forth between chat for my front-end workflow, so I shipped something to fix it. Introducing Inspector Comments! You can now click and drag anything on the page to add a comment and an agent will take care of the rest ...and toggle between before/after views.

@h2oai #AgenticAI is World #2 on @Futurex AI benchmark "Can AI predict the future? The next frontier for LLM Agents!" futurex-ai.github.io using #OpenAI #GPT5 #h2oGPTe cc @pseudotensor @mmalohlava