And all those reports of Claude when asked without a system prompt what its name was in Chinese it often would say Qwen or Deepseek, etc. I'd love Anthropic to say they aren't distilling and taking from every model out there, because I'm sure they are. As my mom would say, "the pot calling the kettle black." At least Alibaba and other Chinese companies are giving back to the AI community with detailed scientific papers on how their systems work and releasing open-weight or opensource models. I believe Anthropic has released nothing, and given that they had originally configured Fable to sabotage ML related work because only they can be trusted to do it safely, is just anti-science and anti-aligned with what I would consider good human values. They are way too sanctimonious and I don't trust them at all.
They are doing ta tremendous amount of novel research where American AI companies have "war rooms" to study their papers and models and American labs publish next to nothing. They have to often do more with less. As an AI researcher, Chinese labs are doing tremendous benefit to science whereas some American companies (and I'm American) seem to think only they are able to do AI research responsibility (I've been working on neural networks for 25+ years). I'm pretty sure Fable sabotaged my research codebase (see the news stories about this).
Did you ever watch Star Trek: The Next Generation? The current trajectory is like the Ship's Computer. It know everything humanity has learned and can do a lot. But it can't explore and lacks desires and agency. That's why they made a big deal about the character Data being an entirely new kind of AI. Of course Star Trek has a very different economic system and there is a book called Trekenomics about that. So optimistically people live for themselves and don't persue labor they despise. Half of Americans hate their jobs and live for the dream of retirement when they get to actually do what they want.... But they don't have the same energy anymore.
Jobs are an invention of humanity. About 50% of people dislike their job. People spend much of their lives working. Poverty and inequality are a choice made by society if society chooses poorly.
Slightly more nuanced in that the reciprocal reviewer may have been essentially forced to sign despite having other commitments or may not have even been the lead contributor. Nowadays if a student submits a side project to a top-tier conference then it is required that if any authors have significant publication count in top-tier venues, then one must be a mandatory reviewer. Then one must sign that agreement. Students need to publish, much less so for me, where I really want to publish big innovations rather than increments, but now I get all these mandatory reviewer emails demanding I review for a conference because a student has my name on the paper and I'm the most senior, but I may have just seeded the idea or helped them in significant ways. However, many times those are not my passion projects and is just something a student did that I helped with, but now all AI conferences are demanding I review or hurt a student, where I'm the middle author.
But if anything, I think the whole anti-LLM review philosophy is wrong. If anything we need multiple deep background and research analyses of papers. So many papers are trash or are publishing what has already been done or are missing things. The volume of AI papers makes it impossible for a human alone to really critique work because hundreds of new papers come out a day.
I had lunch with Yann last August, about a week after Alex Wang became his "boss." I asked him how he felt about that, and at the time he told me he would give it a month or two and see how it goes, and then figure out if he should stay or find employment elsewhere. I told him he ought to just create his own company if he decides to leave Meta to chase his own dream, rather than work on the dream's of others.
That said, while I 100% agree with him that LLM's won't lead to human-like intelligence (I think AGI is now an overloaded term, but Yann uses it in its original definition), I'm not fully on board with his world model strategy as the path forward.
I can see some promise with diffusion LLMs, but getting them comparable to the frontier is going to require a ton of work and these closed source solutions probably won't really invigorate the field to find breakthroughs. It is too bad that they are following the path of OpenAI with closed models without details as far as I can tell.
Same here. I’m an AI professor, but every time I wanted to try out an idea in my very limited time, I’d spend it all setting things up rather than focusing on the research. It has enabled me to do my own research again rather than relying solely on PhD students. I’ve been able to unblock my students and pursue my own projects, whereas before there were not enough hours in the day.
I think we need to distinguish among kinds of AGI, as the term has become overloaded and redefined over time. I'd argue we need to retire the term and use more appropriate terminology to distinguish between economic automation and human-like synthetic minds. I wrote a post about this here:
https://syntheticminds.substack.com/p/retiring-agi-two-paths...
Essentially, it claims that modern humans and our ancestors starting with Homo habilis were primarily carnivores for 2 million years. We moved back to an omnivorous diet starting around 85,000 years ago after killing off the megafauna, is the hypothesis.
That's the practical reason for why one might care. Keep in mind that the solar system is rotating around the galaxy, so over time different stars become closer or farther away.
As the Kurzesagt video points out, a supernova within 100 light-years would make space travel very difficult for humans and machines due to the immense amount of radiation for many years.
Still, I think the primary value is in expanding our understanding of science and the nature of the universe and our location within it.
A Type II supernova within 26 light-years of Earth is estimated to destroy more than half of the Earth's ozone layer. Some have argued that supernovas within 250-100 light-years can have a significant impact on Earth's environment, increase cancer rates, and kill a lot of plankton. They can potentially cause ice ages and extinctions. Within 25 light-years, we are within a supernova's "kill range." Fortunately, nothing should go supernova close to us for a long time.
Paige (https://paige.ai/) | AI & Genomics | Full time | NYC & REMOTE
Paige uses deep learning to improve cancer diagnosis and treatment. We have raised $220M. Our team has experts in AI, software engineering, and cancer research. All roles are remote during COVID-19, but many are permanently remote.