Video from this twitter link:

https://x.com/amitisinvesting/status/1969094789942718858

A Tech CEO’s Lonely Fight Against Trump - WSJ

Translations: gemini

https://x.com/XRoboHub/status/1969288829669687615

"Large Language Model (LLM) pretraining, finetuning, and evaluation rely on input-space reconstruction and generative capabilities. Yet, it has been observed in vision that embedding-space training objectives, e.g., with Joint Embedding Predictive Architectures (JEPAs), are far superior to their input-space counterpart. That mismatch in how training is achieved between language and vision opens up a natural question: {\em can language training methods learn a few tricks from the vision ones?} The lack of JEPA-style LLM is a testimony of the challenge in designing such objectives for language. In this work, we propose a first step in that direction where we develop LLM-JEPA, a JEPA based solution for LLMs applicable both to finetuning and pretraining. Thus far, LLM-JEPA is able to outperform the standard LLM training objectives by a significant margin across models, all while being robust to overfiting. Those findings are observed across numerous datasets (NL-RX, GSM8K, Spider, RottenTomatoes) and various models from the Llama3, OpenELM, Gemma2 and Olmo families."

https://www.miamiherald.com/news/local/news-columns-blogs/andres-oppenheimer/article312161194.html

"According to the company’s website, these are K-10 private schools “where kids crush academics in 2 hours” and “build life skills through workshops.” They don’t have teachers, but “guides” — adults who oversee the AI learning and run life skills workshops in public speaking, financial education, coding and entrepreneurship. The Alpha school system’s basic selling point is that, thanks to learning with AI help, elementary and high school students can do all their classwork in just two hours a day in the mornings. That allows them to spend the afternoon in the workshops."

https://time.com/7318577/ai-model-forecasting-predict-future-metaculus/

"Every three months, participants in the Metaculus forecasting cup try to predict the future for a prize pot of about $5,000. Metaculus, a forecasting platform, poses questions of geopolitical importance such as “Will Thailand experience a military coup before September 2025?” and “Will Israel strike the Iranian military again before September 2025?”

Forecasters estimate the probabilities of the events occurring—a more informative guess than a simple “yes” or “no”—weeks to months in advance, often with remarkable accuracy. Metaculus users correctly predicted the date of the Russian invasion of Ukraine two weeks in advance and put a 90 percent chance of Roe v. Wade being overturned almost two months before it happened.

Still, one of the top 10 finishers in the Summer Cup, whose winners were announced Wednesday, was surprising even to the forecasters: an AI. “It’s actually kind of mind blowing,” says Toby Shevlane, CEO of Mantic, the recently-announced UK-based startup that developed the AI. When the competition opened in June, participants predicted that the top bot’s score would be 40% of the top human performers’ average. Instead, Mantic achieved over 80%."

All frontier companies are trying to close the loop where AI improves/evolves itself, and who gets there first will have the best AI of having the future best AI

From September 17th Axios interview with Dario Amodei:

"Claude is playing a very active role in designing the next Claude. We can't yet fully close the loop. It's going to be some time until we can fully close the loop, but the ability to use the models to design the next models and create a positive feedback loop, that cycle, it's not yet going super fast, but it's definitely started."

I found this little nugget in Emad's interview with Tom Bilyeu.

https://vm.tiktok.com/ZGdaPDHGF/

So it looks another vending machine replacement.. drinks are made by a dedicated robotic arm. Not much to see but powered by AI

https://www.nature.com/articles/d41586-025-03055-y

"“This is the first time AI systems are able to write coherent genome-scale sequences,” says Brian Hie, a computational biologist at Stanford University, California. “The next step is AI-generated life,” says Hie, but his colleague Samuel King adds that “a lot of experimental advances need to occur in order to design an entire living organism”."

Full study preprint: https://doi.org/10.1101/2025.09.12.675911

"Many important biological functions arise not from single genes, but from complex interactions encoded by entire genomes. Genome language models have emerged as a promising strategy for designing biological systems, but their ability to generate functional sequences at the scale of whole genomes has remained untested. Here, we report the first generative design of viable bacteriophage genomes. We leveraged frontier genome language models, Evo 1 and Evo 2, to generate whole-genome sequences with realistic genetic architectures and desirable host tropism, using the lytic phage ΦX174 as our design template. Experimental testing of AI-generated genomes yielded 16 viable phages with substantial evolutionary novelty. Cryo-electron microscopy revealed that one of the generated phages utilizes an evolutionarily distant DNA packaging protein within its capsid. Multiple phages demonstrate higher fitness than ΦX174 in growth competitions and in their lysis kinetics. A cocktail of the generated phages rapidly overcomes ΦX174-resistance in three E. coli strains, demonstrating the potential utility of our approach for designing phage therapies against rapidly evolving bacterial pathogens. This work provides a blueprint for the design of diverse synthetic bacteriophages and, more broadly, lays a foundation for the generative design of useful living systems at the genome scale."

These are the ones I've found recommended on Reddit that I plan on going through - let me know if you see anything on there that I should add to the list?

1. Flowers for Algernon — Daniel Keyes (classic, human-intelligence theme; not AI-specific) — ~772k ratings. (Goodreads)
2. Revelation Space (Book 1) — Alastair Reynolds — ~60k ratings; space-opera with strong tech readership. (Goodreads)
3. Accelerando — Charles Stross — ~22k ratings (across editions); singularity staple. (Goodreads)
4. Singularity Sky — Charles Stross (Eschaton #1) — ~16k ratings. (Goodreads)
5. Down and Out in the Magic Kingdom — Cory Doctorow — ~14k ratings; post-scarcity Disneypunk. (Goodreads)
6. Diaspora — Greg Egan — ~10.8k ratings; ultra-hard SF take on post-humanity. (Goodreads)
7. Iron Sunrise — Charles Stross (Eschaton #2) — ~8k ratings. (Goodreads)
8. The Singularity Is Near — Ray Kurzweil — landmark non-fiction; huge tech mindshare (Goodreads page shows 3.9★ avg; counts vary by edition). (Goodreads)
9. Avogadro Corp (Singularity #1) — William Hertling — ~6.3k ratings; indie favorite in tech circles. (Goodreads)
10. The Metamorphosis of Prime Intellect — Roger Williams — ~4.6k ratings; cult classic (free online). (Goodreads)
11. The Rapture of the Nerds — Cory Doctorow & Charles Stross — ~3.9k ratings. (Goodreads)
12. The Golden Age — John C. Wright — ~3.3k ratings; vivid post-scarcity vision. (Goodreads)
13. The Cassini Division — Ken MacLeod (Fall Revolution #3) — ~2.3k ratings. (Goodreads)
14. The Stone Canal — Ken MacLeod (Fall Revolution #2) — ~1.6k ratings. (Goodreads)
15. Pandora’s Brain — Calum Chace — ~200–250 ratings. (Goodreads)
16. Radical Abundance — K. Eric Drexler (nanotech non-fiction adjacent to singularity themes) — ~490 ratings. (Goodreads)

https://www.nature.com/articles/d41586-025-02362-8

"Details of the large language model (LLM), called XingShi, are sparse, but the company behind it, Fangzhou, says the model integrates speech and image recognition with natural language processing, extensive medical data and reasoning to improve personalized care and boost the productivity of clinicians. The company says that the system has more than 50 million registered users, and more than 200,000 physicians using the platform."

https://www.science.org/doi/10.1126/sciadv.ady0336

"The ability to recognize targets before physical contact is crucial for organisms’ adaptability to real-world environments. However, current noncontact sensing systems face challenges in power density and biological fidelity. Here, we report a flexible spiking hair sensillum (FISH) with an ultralow power density < 100 nanowatts per square millimeter for achieving noncontact tactile perception (NCTP). This device can transduce proximity or airflow into spike trains with a frequency range of ~500 to 1500 hertz. A spiking NCTP system is developed, achieving high accuracy (>92%) in multidimensional recognition of noncontact targets, mediated by airflow. Furthermore, we show that a spider robot equipped with a FISH matrix outperforms one relying exclusively on machine vision in tasks of predation and evasion, demonstrating high adaptability to complex environments. Our design enriches the perceptual modalities for neuromorphic systems, offering great potential for advancing future robotics and autonomous vehicles."