Manthan Sheth

Singapore's FM. Very blunt on Trump: - "the underwriter of this world order has now become a revisionist power, and some people would even say a disruptor" - "the entire global economy has been taken hostage and we will all pay a price on hostilities" mfa.gov.sg/newsroom/press…

Japan is the BIGGEST WINNER My piece: open.substack.com/pub/zinebribou…

18% of global air freight capacity has been taken out of the market by conflict in the Middle East this weekend.

Trump’s war of choice is actually making China and Russia look like more mature great powers that respect the rules-based international order.

What did removing Saddam, Gaddafi, Assad get us? Chaos, civil war, genocide. The rule for regime change operations in the Middle East is that they don’t flip a country from bad-to-good. They flip a country from bad-to-worse.

Machine learning is the key technology underlying today’s AI systems. On Feb. 23, @DigEconLab Digital Fellow Tom Mitchell will explore its history, from key scientific breakthroughs to some of the surprises and dead-ends along the way. Don't miss it: digitaleconomy.stanford.edu/event/tom-mitc…

My "Math, Revealed" series is freely available to anyone -- no paywall! -- in the thread below

My first work on metalearning or learning to learn came out in 1987 [1][2]. Back then nobody was interested. Today, compute is 10 million times cheaper, and metalearning is a hot topic 🙂 It’s fitting that my 100th journal publication [100] is about metalearning, too. [100] Kazuki Irie, @robert_csordas, J. Schmidhuber. Metalearning Continual Learning Algorithms. Transactions on Machine Learning Research (TMLR), 2025. [2] AI Blog (2020). Metalearning Machines Learn to Learn (1987-) [1] J. Schmidhuber. Evolutionary principles in self-referential learning, or on learning how to learn: the meta-meta-... hook. Diploma thesis, TU Munich, 1987.

@hamptonism Citadel is definitely multi strat.

Hedge Fund Strategies:

🚧 High-quality, diverse data is a major bottleneck in robot learning. 🌎🤲 DexWild offers a fast, scalable way to collect human demonstrations in-the-wild — unlocking real-world generalization for robots! #CMUrobotics

Agreeing to this “premature” ceasefire will go down as one of Modi’s greater strategic blunders. An unnatural islamofascist pseudo state such as Pak has only nuisance value to provide by way of its existence. There lay an opportunity to reliably fix that & open up new avenues.

The best way to learn #machinelearning is to: Avoid popular content that oversimplifies concepts, especially when written by individuals with no real ML experience. Dive into high-quality books and work through them diligently.

Excited to share that our paper, "Multi-Robot Motion Planning with Diffusion Models," has been selected for a Spotlight presentation at #ICLR2025!🔦🤖 We scale diffusion planning to dozens of robots *without* multi-robot data by using search. Project: multi-robot-diffusion.github.io 🧵

hi infra ppl - some updates on cs153.stanford.edu that @mabb0tt and i are teaching this quarter: 1. lots of people asked if there'll be a live stream. as of now, we don't have plans to do a live stream, but we'll record and post the lectures online (as long as each speaker is okay with that), ideally within a couple days of each lecture. right now, we only have 1 course assistant and 180+ students, so pls bear with us as we figure out how to handle ops 2. @mntruell is now our latest addition to the speaker lineup! and, his lecture will be up online - i'm sure people are going to love it. the @cursor_ai team is on the frontlines of ai application scaling, with tons of painfully earned valuable lessons for the infra community

blog.ml.cmu.edu/2024/12/06/scr… A critical question arises when using large language models: should we fine-tune them or rely on prompting with in-context examples? Recent work led by @JunhongShen1 and collaborators demonstrates that we can develop state-of-the-art web agents by fine-tuning open-source LLMs. Read more in our latest blog post!

- Pentagon can’t fully account for $824 Billion - $236 Billion in improper payments in federal programs in 2023 - $200 Billion in pandemic relief went to fraud/abuse - The U.S. failed to track $1 Billion in Ukraine Aid How much do we not yet know about?

The second time in a year that a Chinese ship is accused of destroying European undersea cables. Nov 2023: "Finland and Estonia are formally investigating a Chinese vessel that drug its anchor over 100 nautical miles though the Gulf of Finland, hitting telecom and gas lines."

Trump's US election victory was music to the ears of some attendees at Singapore's FinTech Festival. But others feared the economic cost of his win. Read more in this week's free Singapore Edition newsletter. trib.al/TS8zCx7

Carnegie Mellon launched its Deeper Conversations series to facilitate free expression and explore different perspectives. This fall, the series focused on the U.S. election, offering the CMU community a space to engage over topics that impact voters. ➡️ cmu.is/Election-Deepe…