Tech Hotspots on X — 2026-06-23

Let me explain what just happened, because I don’t think people realize how INSANE this is. > Cortical Labs put 200,000 real human brain cells onto a silicon chip and trained them to play Doom in just one week. > Each CL1 system costs $35,000. > A rack of 30 units consumes only 850–1,000 watts combined. > The human brain operates on 20 watts. > Large AI training clusters burn through megawatts. >Backed by In-Q-Tel. 115 units began shipping in 2025. > Cortical Labs is selling “Wetware as a Service” through Cortical Cloud, letting developers deploy code remotely to living human neurons with no lab required, > priced like a software subscription but powered by real brain cells grown from adult skin and blood samples. > it isn’t about gaming, it’s about biological computing that could eventually outperform traditional silicon in energy efficiency and adaptability. This is getting really scary and we’re still at the very beginning.

Water usage has been a hot topic in the AI data center world, but the numbers may surprise you. According to the Manhattan Institute, data centers use 0.2 percent of daily water usage in the U.S. and that number has dramatically decreased in the past few years due to a new method: liquid cooling. By moving to 45°C liquid cooling, AI factories in favorable climates can use dry coolers instead of conventional cooling-tower-based systems, cutting facility cooling water use from roughly 2.6M gallons per MW per year to near zero. Liquid cooling enables AI factories to be both water and energy efficient, while creating opportunities for heat reuse and dispersal to local communities, allowing these factories to become energy grid assets. Learn more below ⬇️ https://t.co/7WanoPNKTR

these two software carried a whole generation of internet https://t.co/wLrlzA7FpH

New in Claude Code: Artifacts. Interactive pages built from your session, like a PR walkthrough or a living project dashboard, shared with your team at a private link. Available in beta on Team and Enterprise plans. https://t.co/0NX9gNCaAs

I’m excited to share that I’ll be joining OpenAI and look forward to working with the exceptional team there. It was a difficult decision to move on. I’m incredibly proud of the amazing team at Google and everything we’ve built together. It has been an honor and a pleasure to work with all of you.

If it’s not clear yet, this is what I think will happen soon. Every major tech company except Apple has announced their own LLM. Apple have spent years perfecting their on-device neural engine. Capable of some absolute insane operations. Loads of compute in a small and energy efficient form factor. With M1, M2 & soon M3 the neural engine is even more powerful than their A series mobile chipsets. While we currently need the cloud to run ChatGPT and it’s clunky, I think Apple is going to blow everyone out of the water here. Both on desktop class hardware and mobile. I think Apple will be launching their own secure and private LLM that runs on device (edge compute). And when necessary it offloads more heavy workloads to a cloud based LLM that’s optimized for heavier tasks. So we will initially have some hybrid. Personal, with tight hardware and software integration this AI will be omnipresent. Apple will probably use this to sell a lot of new hardware that they claim is needed to run this. They will make a lot of moneys. For me the LLM’s will form the new protocol level technology upon which most new software will be built. We will have to re-wire our core understanding about what an application is. Single-use apps will be a huge thing. If you need to solve a unique problem, and nobody has ever done software for that because not enough market. With an LLM even a problem with only one user, will be doable, enter your ask, and code gets written, problem gets solved. Runtime ends, app dies. Done. Single use apps are born. It’s hard to predict or try to understand how the world will look just 10 years from today. It will be very different, we have passed the inflection point, the rocket engines have been lit. We’ve taken off. Add to all the above that every single field, category and market will be disrupted at the same time. And not only with text/coding but with any multi-media we have. Images, video & audio. Anything we can come up with can and will be enhanced or disrupted by AI. Once we got more people that will have their AI A-ha moment the rate of change and adoption will continue to increase. This will continue until we have global access and coverage. People will get left behind, and this will be one of the most important things to try to combat. Having a 0% left behind policy. We need to make sure AI benefits all. We’re living through a paradigm shift, and we’re witness a new protocol level technology. We’re seeing it arrive in real-time and most people have no clue about what’s about to happen. I’m not an AI alarmist, I’m an AI gardener, and optimist. We will have time to adapt. Not as long as we had during the Industrial Revolution, but enough time to make sure we have a chance at a positive outcome. We’re moving away from the Information Age into the Age of Intelligence. With unlimited access to intelligence anywhere, anytime. 18th Mars 2023 - Linus Ekenstam

• be Morris Chang • survive WWII in China, escape to America in 1949 • go to MIT, fail the PhD qualifying exam twice • decide academia is a trap, join Texas Instruments • spend 25 years climbing the ranks, building their entire semiconductor division into a global powerhouse • get passed over for the CEO job because of corporate politics • 1985: you are 54 years old. Most executives are buying golf clubs and preparing to retire. • the Taiwanese government begs you to move to a tiny island and build their tech sector from scratch • you look at the global chip industry and see a massive, glaring inefficiency • the industry rule at the time: "Real men have fabs" (if you want to design chips, you have to spend billions to build the factory to make them) • Chang realizes: "What if a factory just prints everyone else's designs, and promises never to compete with them?" • 1987: founds TSMC (Taiwan Semiconductor Manufacturing Company) at age 56 • invents the "pure-play foundry" model • traditional hardware giants like Intel and IBM laugh at him for just doing the "dirty work" • suddenly, a guy named Jensen Huang (NVIDIA) and companies like Apple realize they can design world-class chips without spending $10 Billion on a factory • TSMC single-handedly births the entire "fabless" technology industry • scales the physics down to the atomic level, printing circuits smaller than a biological virus • becomes an absolute, unbreakable monopoly on advanced human technology • accidentally builds a "Silicon Shield" around Taiwan • the US and China both realize that if Morris Chang's factories go offline for a single week, the entire global economy (smartphones, fighter jets, AI, car manufacturing) instantly collapses • steps down, comes out of retirement at age 78 during the 2008 financial crisis to ruthlessly fire the CEO, doubles R&D spending while everyone else is panicking, and permanently crushes Intel • 94 years old, smokes a pipe, plays competitive bridge, and controls the single most important bottleneck on planet Earth "We do not compete with our customers. We are everybody's foundry."

study semiconductor manufacturing not to build a fab. not to get a job at TSMC. but to witness how far the human mind has gone. photolithography is pure magic disguised as engineering. we’re literally etching patterns smaller than viruses; using light, mirrors, gases, plasma, and math. machines that cost billions; all to place atoms exactly where we want them. a chip isn’t just silicon. it’s the story of precision, obsession, and human imagination pushed to its limit. study how semiconductors are made; because it’s not just technology, it’s a love letter to what humans can do when they decide to understand everything.

Genuinely impressed, almost shocked, at how good GLM-5.2 by @zai_org is at coding. This changes things.