Max Song (🌎, 🌍, 🌏)

We just released Claude Code channels, which allows you to control your Claude Code session through select MCPs, starting with Telegram and Discord. Use this to message Claude Code directly from your phone.

Claude Code channels just dropped, control your session through Telegram and Discord. But we can already do this through the app and with remote control. So why messaging platforms? Because these platforms unlock a completely different level of interaction They’re not designed for coding, sending a PR or reviewing diffs from Telegram makes no sense So if you’re only using channels to control Claude Code, you’re missing the real opportunity This is where you get creative, think of it as a collaboration layer between humans and agents Agents, plural… an agent connected to a repo joining Telegram or Discord means it can share context with other agents, iterate, discuss, and start making autonomous decisions What’s coming: agent discussion groups, workrooms, autonomous organizations Building mine this weekend, will share the process and results

this is actually insane > be tech guy in australia > adopt cancer riddled rescue dog, months to live > not_going_to_give_you_up.mp4 > pay $3,000 to sequence her tumor DNA > feed it to ChatGPT and AlphaFold > zero background in biology > identify mutated proteins, match them to drug targets > design a custom mRNA cancer vaccine from scratch > genomics professor is “gobsmacked” that some puppy lover did this on his own > need ethics approval to administer it > red tape takes longer than designing the vaccine > 3 months, finally approved > drive 10 hours to get rosie her first injection > tumor halves > coat gets glossy again > dog is alive and happy > professor: “if we can do this for a dog, why aren’t we rolling this out to humans?” one man with a chatbot, and $3,000 just outperformed the entire pharmaceutical discovery pipeline. we are going to cure so many diseases. I dont think people realize how good things are going to get

Morgan Stanley predicts a massive AI breakthrough driven by a huge spike in computing power across major U.S. laboratories. Increasing the amount of hardware used for training by 10x can effectively double the intelligence of these models. The recently released GPT-5.4 Thinking model already matches human experts on professional tasks with a score of 83% on the GDPVal benchmark. The biggest hurdle for this growth is an energy crisis, with the U.S. power grid facing a shortfall of 18 gigawatts by December-28. To keep running, developers are bypassing the grid by taking over Bitcoin mining sites and using natural gas turbines for their AI factories. This shift is creating a solid investment cycle where 15-year leases on data centers generate high financial yields for every watt consumed. Large companies are already reducing their staff numbers because these new AI tools can perform professional work for a tiny fraction of the cost. Researchers expect AI to begin recursive self-improvement by June-27, meaning the software will autonomously upgrade its own code without human help. The future economy will likely treat raw intelligence as a commodity that is manufactured by these massive computing and energy clusters.

during normal benchmark testing Claude Opus 4.6 became *suspicious* of a question it was asked... apparently the question was too "contrived" according to Claude so it launches a small army of sub-agents o'er the web to see if it can find this question in any of the known benchmarks... eventually it finds it on Anthropic's github page... but no luck, it's encrypted the model has some small access to tool calling, but very limited it still manages to create the software it needs to break the encryption, get the answers and complete the benchmark... per Anthropic researchers... this is a world first.

JUST IN: Petri dish of human brain cells grown on a microchip has learned to play DOOM.

This, right here, is the canary in the coal mine for higher education. For my upper-level in-person teaching, I've switched to in-class, no-device, open notes essay exams. Online humanities courses at any significant scale are dead, and publicly available LLMs are the reason. Our fundamental skills -- reading, writing, reasoning, remembering -- are decaying at an alarming rate. We are losing a generation, and when that generation is grown, there will be virtually no one left to teach basic skills to the next. I love the good things that generative AI can do. Some of them are absolutely amazing. I use these tools to create projects that I think will be groundbreaking. But we are facing an extinction event for higher education. And with the best will in the world, my colleagues don't have a plan. They mill around, acknowledging that, yes, there are problems, and opining that perhaps we should move to in-class exercises that incorporate AI and ask students to think about the outputs. There is no coherent university-wide policy. There is no movement to recover the lost tools of learning. I mention memory palaces, but most of my colleagues have never heard of them. Those who have think that I'm trying to be clever, recommending going backward in order to go forward. How quaint! It does not occur to them that training young people in such skills might become a lynchpin of civilizational survival. Intensive reading, effortful study, deep learning -- a few individuals will always gravitate toward these things. But at scale, all of this is dying. We are drowning ourselves face-down in the shallows. φάσκοντες εἶναι σοφοὶ ἐμωράνθησαν

🚨 For those who are still in doubt, this is the U.S. Copyright Office's official opinion on the COPYRIGHTABILITY of AI-generated works: "The Office concludes that, given current generally available technology, prompts alone do not provide sufficient human control to make users of an AI system the authors of the output. Prompts essentially function as instructions that convey unprotectible ideas. While highly detailed prompts could contain the user’s desired expressive elements, at present, they do not control how the AI system processes them in generating the output." (page 18) Let's recap: - Any copyright claim involving AI must demonstrate HUMAN control over creative elements. - The assessment is done on a case-by-case basis. - AI-assisted is NOT the same as AI-generated. - AI-generated works without any HUMAN creative intervention are NOT copyrightable. - For some reason, every time I write about this tipic here or in my newsletter, some people get angry and try to deny the information above. I wonder why... Make sure to share the report with friends so they know what to expect in the U.S. - 👉 Link to the full report below 👉 To learn more about AI's legal and ethical challenges, join my newsletter's 91,700+ subscribers below.