HN user
Thank you! Parr, Pezzulo & Friston looks like the kind of book I'm after - love cross-disciplinary works. After all, knowledge and nature are continuous. It's humans who like to chop them up into subfields :)
Tangentially related: It appears that TD ideas pop up in diffusion models, VAEs and neural net training dynamics. Any author/reading advice on links between thermodynamics, information, and neural nets?
Yep, it's the early days. Eventually we'll work out something like Design Patterns for Hybrid Development, where humans are responsible for software architecture, breaking requirements into maintainable SOLID components, and defining pass/fail criteria. Armed with that, LLMs will do the actual boilerplate implementation and serve as our Rubber Ducky Council for Brainstorming :)
Agree. We've seen cowboy developers who move fast by producing unreadable code and cutting every corner. And sometimes that's ok. Say you want a proof of concept to validate demand and iterate on feedback. But we want maintainable and reliable production code we can reason about and grasp quickly. Tech debt has a price to pay and looks like LLM abusers are on a path to waking up with a heavy hangover :)
But why would you want to review long AI PRs in the first place? Why don't we apply the same standards we apply to humans? Doesn't matter if it was AI-generated, outsourced to Upwork freelancers or handcrafted in Notepad. Either submit well-structured, modular, readable, well-tested code or PR gets rejected.
Can you elaborate on the "mode of peril"? Is it:
(a) Top labs quietly signing deals for military deployment of frontier models in unmanned strike weapons?
(b) Top labs agreeing to license LLMs for social engineering/propaganda ops?
(c) Models that vastly exceed human intelligence and have capacity to pursue own agenda (i.e. runaway intelligence)?
(d) Something else?
It looks like dangers of AGI are overblown (perhaps partially due to grant funding and ability to get political traction/investment/competitive advantage), while (a) and (b) are severely underdiscussed. Would love to get other perspectives.
At ~9:50 Michael Moritz talks how the 100-year media history tells us that if you can gather a large audience in one place, you will be able to sell them advertising.
It's likely that Google will not be the last search company. What business model could a successor use to generate revenue without falling into the ad trap? Why didn't early search engines choose other models like subscription, revenue sharing with telecom companies, or turning queries into marketing signals for manufacturers/merchandisers?
While John talks about the period before Google, this quote brings up a remarkable déjà-vu:
[~14:30] Although the search companies were having great success, they were turning into something quite different than what they started out to be. They lost the sight of what brought users to them in the first place: The need to find things. The search engine companies stopped caring about search.
When it came to actually locating relevant information on the web, Yahoo, Excite, and the rest of the so called search companies, frankly, stunk. You could spend all day typing various combinations of keywords that you were looking for. Most of the results were links to sites trying to sell you something you didn't want. The world was hungry for a radically better way of searching the web.
Reading these answers reminded me why I love HN - actually thoughtful perspectives :) Guess a lot boils down to two variables - (a) suggestion UX quality and (b) definition of 'rejection' event. I skimmed through the paper and it turns out that 91% figure is based on feedback from 70 people and anonymous feedback wasn't allowed. So, 'overwhelming 91% favorable' can be paraphrased to `64 people out of the total 16k user base said they liked it'. Would be interesting to see indirect metrics like retention on day 15.
The abstract says ..we present metrics from our large-scale deployment of CodeCompose that shows its impact on Meta's internal code authoring experience over a 15-day time window, where 4.5 million suggestions were made by CodeCompose. Quantitative metrics reveal that (i) CodeCompose has an acceptance rate of 22% across several languages, and (ii) 8% of the code typed by users of CodeCompose is through accepting code suggestions from CodeCompose. Qualitative feedback indicates an overwhelming 91.5% positive reception for CodeCompose.
In other terms, out of 4.5 million suggestions about 80% were off, yet there is 91% positive reception. That's 3.6 million rejected suggestions that potentially distracted programmers from doing their work. Yet users are happy. Is there a contradiction in these figures?
What's the value of bringing Facebook/Instagram mechanics into HN? Wouldn't that skew social dynamics away from egalitarianism, giving rise to "influencers", social bubbles and rise in clickbait? I think that not having a 'follow your friends' mechanism is a feature of HN.
Depending on your use case and willingness to hack, there are plenty of alternatives. E.g. take a look at this list: https://archive.is/x5K4o
My impression is that many places that label themselves as hacker/maker spaces are some version of a commercial coworking space with equipment. They have the tools, but not the spirit. That's why I mentioned Noisebridge and CCL. E.g. in CCL you can join open projects like making cheese without milk. That's quite different than 'pay membership fee X, here's the equipment, do what you want'.
Do you know of specific places in Europe that capture that spirit? With both diversity and depth of knowledge in different disciplines?
+1 for IEEE Spectrum. I recently stumbled upon print issue archive from 2010-2012 and was delighted by their coverage of private space flight and 3D printing. To me, Spectrum is an early high-level overview of interesting technology.
Turns out Patrick Breyer from the Pirate Party already put up a list of practical steps, infographics and EP members, see https://www.patrick-breyer.de/en/posts/chat-control/#WhatYou...
Sounds like an "NLP valley" with Prof. Ney as Aachen's own Fred Terman :)
Thanks for sharing. Cool to see someone from Aachen NLP group. I'll be visiting Aachen/Düsseldorf/Heidelberg area in spring. Do you know of any local ML meetups open to general (ML engineer/programmer) public?
Here it is: https://news.ycombinator.com/item?id=34641359
Perhaps write letters to members of European Parliament explaining our concerns, then ask all our friends to do the same?
To make it a low-cost effort, we could (a) prepare a list of relevant politicians (b) create a template of the letter. Then our non-technical friends need only sign and mail this. And if we put this all up as a one-pager on GitHub pages, it's suitable for sharing on social networks too ;)
Sometimes I feel that the world is sleepwalking straight into the pages of 1984. Proposals to monitor chats, ban encryption, legitimize location tracking create perfect infrastructure for new dictators. If some day a new Hitler grabs power in a nuclear-capable country, he'll be able to track down and destroy dissenters before they have a chance to protest.
What are some simple and practical actions any EU citizen can take now to stop this from going forward?
About 10 years ago I quit a software architect job to start a startup (it failed). Not FAANG, but safe and well-renumerated for my area. If I could go back in time, I'd quit again without thinking. It was a rut.
However, this isn't universal advice. There are people who don't want/like risk. They want a safe and steady job that gives them status, preferably without too much stress and a good salary. In exchange they agree to play corporate office games and doing less exciting work. And that's ok.
The key is (a) figuring out what you want and what kind of person you are, (b) accepting that life is a probabilistic endeavor and you can't take risk out of it. Why do you want to go into ML? Are you hacking something in your spare time? Is it because it seems cool and trendy? Can you go into an ML role at your current workplace?
Politics will be influenced. You can't trust anything you see anymore
How much could you trust media content previously? Staged footage, false narration, biased coverage are nothing new. A counter-intuitive side-effect of opening the Pandora's box could be a realization that media is a form of simulation. Perhaps this will lead more people to filter what they see through a prism of critical thinking.