Don't watch any kind of screen in the evening. Read a book instead. You'll fall asleep sooner.
HN user
martingoodson
martingoodson at gmail space com Chief scientist at Evolution.AI
"Conclusions: This meta-analysis confirmed that skipping breakfast is associated with overweight/obesity, and skipping breakfast increases the risk of overweight/obesity. The results of cohort studies and cross-sectional studies are consistent. There is no significant difference in these results among different ages, gender, regions, and economic conditions."
People seem to be misunderstanding this paper. It doesn't claim that any previous papers have overestimated contamination. That would only happen if scientists didn't routinely use blanks as a comparison, which they do. E.g. "A procedural filter blank was created during each sample batch and analysed alongside the samples, to enumerate potential contamination that could have been introduced during the extraction process."
https://eprints.soton.ac.uk/476076/1/1_s2.0_S014765132300286...
Title needs to be changed. It completely misrepresents this research. There was no comparison between human written and AI written stories.
Honestly, I think if I wasn't there, she still would have loved it. She related to it like a person.
I played with this last night with my four-year old daughter. We had fun with asking Miles to explain what bones are made of etc.
Today, she asked "where has that robot guy gone?". Crying now because I won't let her talk to Miles anymore.
She has already developed an emotional connection to it. Worrying indeed.
Written by someone who knows what they are talking about.
I've worked in data extraction from documents for a decade and have developed algorithms in the space. I've developed a product using LLMs for this purpose too.
This article is essentially correct.
I work in financial data and our customers would not accept 96% accuracy in the data points we supply. Maybe 99.96%.
For most use cases in financial services, accurate data is very important.
We hosted Ziming Liu at the London Machine Learning Meetup a few weeks ago. He gave a great talk on this fascinating work.
Here's the recording https://youtu.be/FYYZZVV5vlY?si=ReoygVJMgY9oje3p
Baptiste Roziere gave a great talk about Code Llama at our meetup recently: https://m.youtube.com/watch?v=_mhMi-7ONWQ
I highly recommend watching it.
Do you have any reference for this claim, or are you guessing? It was reported that the algorithm was a Gradient Boosting Machine by investigators who gained access to the code.
https://www.lighthousereports.com/suspicion-machines-methodo...
I think because it's a relatively 'younger' field, there is a bit more need to know about the foundations in AI than in programming. You hit the perimeters a bit more often and need to do a bit of research to modify or create a model.
Whereas it's unlikely in most programming jobs you would need to do any research into programming language design.
Not at all. It's something I've seen in practice over many years. Neither skill set is 'better' than the other, just different.
There is a need for people who are able to build using available tools, but who don't have an interest in the theory or foundations of the field. It's a valuable mindset and nothing in my original comment suggested otherwise.
It's also pretty clear that many comments on this post divide into the two mindsets I've described.
Most comments here are in one of two camps: 1) you don't need to know any of this stuff, you can make AI systems without this knowledge, or 2) you need this foundational knowledge to really understand what's going on.
Both perspectives are correct. The field is bifurcating into two different skill sets: ML engineer and ML scientist (or researcher).
It's great to have both types on a team. The scientists will be too slow; the engineers will bound ahead trying out various APIs and open-source models. But when they hit a roadblock or need to adapt an algorithm many engineers will stumble. They need an R&D mindset that is quite alien to many of them.
This is when an AI scientists become essential.
It's not about critical thinking: the employees were about to sell up to $1B of shares to thrive capital. This debacle has derailed that.
Sorry! Here's the paper https://arxiv.org/abs/2307.10169
We discussed this at our meetup last night. See here for paper reference and subscribe to get an alert when the recording is uploaded: https://www.meetup.com/london-machine-learning-meetup/events...
The deeper problem here is that review sites don't work well for things as personal as books. I've read many books based on excellent reviews in amazon, and hated many of them. Most people don't have the same taste as me. Likewise many people hate the books I love, and give one star reviews to them.
What's the solution to this?
This is to misunderstand Miles Davis. The point is that he treated the trumpet player with respect, as if he was taking to a trumpet player, not a child. He was engaging with a group of peers. The evidence for this is that he went on the hire the keyboard player, who was 16 years old, to play in his band a year later.
This new law is irrelevant to these points. Vertebrate animals were already considered sentient in UK law. So sharks, dolphins, turtles, fish etc were already covered.
Your outrage comes several years too late.
Sorry for not being clear enough. The point is that this £100M is very likely to be spent on the Turing Institute since it seems to suck up all AI funding in the UK. It will therefore likely be wasted.
That's a good point. Thank you. Officially the open source model was released by the Ludwig Maximilian University of Munich’s CompVis lab. I agree that's something of a technicality.
Of course there are pockets of good work, like in any research institute. It's difficult to point to anything really pushing the envelope in AI research though. You have any evidence to the contrary?
The failure to do any meaningful work related to the most important breakthrough in AI ever is objectively bad.
Because it's irrelevant to the point I'm making in the piece. Like I wrote, lack of infrastructure can be fixed with funding. The other issues can't.
In case anyone takes this comment seriously:'There is strong evidence that processed meat and red meat intake increases risk of colorectal cancer.[31][32][33] The American Cancer Society in their "Diet and Physical Activity Guideline", stated "evidence that red and processed meats increase cancer risk has existed for decades, and many health organizations recommend limiting or avoiding these foods."[34]'
This is from Wikipedia. References are to solid science. Not to YouTube influencers.
This isn't a particularly high quality study. Eg no Statistical power sample size calculation done beforehand.
The 'fuss' is probably what caused Twitter to change their policy on this. The 'fuss' is why people like you can now search the uncensored results, two days after the censorship was first reported.
Yes I checked. He doesn't appear. Someone with 15 followers appears instead. And Elon Musk. https://drive.google.com/file/d/1eowMi0P84lXom3jAxzJwaDC7gfM...
Do you have a screenshot of your results?