Hussain Tech Explorer
@TechHussainE
AI & ML Enthusiast @Cisco. Always exploring 🧠 and loving 🐕 life.
What is longest (i.e. largest) number of thinking tokens that current frontier models think for? (Note that “number of thinking tokens” is often much larger than “context length” because previous thinking tokens get summarized & pre-appended when context length is exceeded)
A curved nitrogen-doped nanocarbon synthesized that can flip shape and trap a gold atom at its center chemistryviews.org/creating-and-m…
Cities of the future will support the digital workforce, provide citizens with personalized experiences, and improve the digital economy. Here are eight forces that will shape the future. @Huawei bit.ly/3eRu799 Rt: @antgrasso #SmartCity #FutureofWork
More than 200 founders and investors have signed an open letter to @RachelReevesMP urging the government to stop the proposed exit tax. The UK tech ecosystem has made phenomenal progress in recent years, and it’s one of the brightest parts of our economy. Introducing…
Starting soon at 8:45AM! All the talks for AI+Science conference at @Caltech will be livestreamed and also available later. aiscienceconference.caltech.edu
today, we’re open sourcing the largest egocentric dataset in history. - 10,000 hours - 2,153 factory workers - 1,080,000,000 frames the era of data scaling in robotics is here. (thread)
Ruxandra has an excellent new post about how the real bottleneck to new medicines is human PoC. Much of the discourse about AI + biology (not Ruxandras post) takes as axiomatic that there nothing to be done to accelerate trials. In fact there is plenty to be done. See China.…
This post is also an argument for why AI won't bail us out of regulatory reform to make in-human testing easier. In fact, in-human data from trials would be the best complement to AI and one way to avoid the "slop trap" by training it on meaningful results.
Since I started working on MLLMs, one question has been nagging at me... MLLMs are evolving incredibly fast. The progress from 2023 to 2025 has been wild. But... are we truly innovating, or just adapting? Think about the recent hot topics: visual reasoning, long video, agents,…
Introducing Cambrian-S it’s a position, a dataset, a benchmark, and a model but above all, it represents our first steps toward exploring spatial supersensing in video. 🧶
Seriously this FibreSeeker 3 Composite Fiber Co-Extrusion is a game changer! 😍 Wimpy little FDMs move over, CFC on the desktop is here! Go look, incredible tech! loyal.ms/fibreseeker3
as someone in uni this feels too real. ai made grades pointless. proving you’re actually good at something is the hard part now. feels like the only move is to build outside the system.
An exciting moment for AI in math! A new paper by a team of mathematicians, including Terence Tao tackled 67 pure math problems and in several cases found solutions that improved on the best-known human results. arxiv.org/abs/2511.02864
Participate in the workshop on mapping & monitoring industries’ transition to climate neutrality on 1 December. To join the conversation driving innovation for Europe's energy-intensive industries, register here: link.europa.eu/CtJVnb
I will be at EMNLP from 4th to 9th in person! Excited to see everyone and would love to have coffee chats!
It’s #EMNLP2025 week! The Cambridge NLIP group is presenting 17 papers across a wide range of topics.🚀 Working on similar problems as the Cambridge NLIP group? Come find our researchers throughout the conference!
.@HRS_hydrogen opens a new subsidiary in Dubai, expanding its #hydrogen refueling network and reinforcing its presence in the Middle East — a key step toward advancing #hydrogenmobility and global decarbonization. #HydrogenNow #Fuelcells #Decarbonise fcw.sh/W2bQEJ
I'll be at #EMNLP2025 this week to present work on making VLMs more robot friendly 🤖 Happy to connect over coffee to chat about VLM steerability, societal impact of AI, or other alignment issues. Also, currently on the job market, looking for industry/postdoc opportunities!
Recruiting PhDs & postdocs for: 🤖 agents "taking over" science (hypogenic.ai and 📌) 🧪 Real scientists ➡️AI (e.g., materials, chem, physics) 📜 Theory + incentives for H-AI collab & credit (e.g., formalizing tacit knowledge) new adventures for me, 🔄 if you can! 🙌
I am hiring for fully funded (up to 3 years) postdoc positions in AI for science at Waterloo/Vector: multimodal deep research, agents, tool-use. You'll work closely w/ industry partners & lead projects. Please share! Apply at r2llab.com/opening or email me directly!
Indeed. Every structure that once existed to serve science - funding, publishing, tenure, peer review - has become an end in itself. The system now rewards performance over progress. Re-centering on science as the goal rather than the credential is exactly what’s needed.
Federal funding was meant to fuel scientific breakthroughs—now it’s a surrogate for impact, and sometimes the endpoint itself. Publishing began as a way to share discoveries—now it’s prestige. Tenure was supposed to protect inquiry—now it’s a status symbol. Peer review was for…
Did you ever want to navigate an 18 story mansion? Well, now you can do that without even retraining your Diffusion Forcing video model. Check the excellent work we did with @ndsong95 @MichalStaryy @BoyuanChen0 @vincesitzmann andrewsonga.github.io/gvs/
GVS also stably scales to longer videos (1080 frames) given more test-time compute, establishing itself as a promising alternative to autoregression for long video generation. Note that this video is generated without any keyframe interpolation! (8/9)
A ‘groundbreaking new synthetic approach’ to Swern oxidation has been developed by a group at the University of Greenwich. What potential does this hold for the future of oxidation? chemistryworld.com/news/a-current…
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