GPT-5: Everything You Need to Know So Far
Was yesterday the day GPT-5 actually started training? This video has everything we think we know so far about GPT-5, drawing on exclusive interviews, OpenAI employee comments, Altman confirmations and more. Think of this as the ultimate compilation of GPT-5 news. Plus, as a bonus, you’ll get 1 super-practical tip on typing to ChatGPT and a Dalle-3 discovery.
AI Insiders:
GPT-5 Training Tweets?:
Altman Gates:
Altman Guessing Game:
OpenAI Cryptic Tweets Ben Newhouse:
Altman Davos:
Altman Axios:
Altman In the Room:
Karpathy OS:
Brockman Checkpoints:
Let’s Verify:
My Original Video on Verify:
Thought Unfaithfulness:
Deepmind Original:
OpenAI Data:
Etched AI 100T Video:
French Dataset:
Peter Wildeford:
GPT-4 Typos:
OpenAI Redteaming:
Brockman Unpredictable:
OpenAI Elections:
Biden Robocall:
Anthropic Amodei Interview:
Laziness:
AI Insiders:
Non-Hype, Free Newsletter:
The thing I love about your channel is you only post when there is news to share, instead of posting filler on a regular schedule to appease the algorithm. The signal to noise ratio of this channel is 💯
Definitely!
Perfect description of why this channel is the best. Completely unrivalled signal to noise.
I find myself trying to scratch the itch for AI Explained content between posts by watching other higher-output channels, but I always come back to this one as my actual source for useful and insightful news.
THIS. Every video is actual news and developments.
Best ai channel by far
Always top tier analysis. I can’t help but feel mildly apprehensive when I picture the capabilities of the next generation of frontier models.
Amazing content as always. I’m also with you regarding Open IA releasing gpt5 at the end of the year. Let’s see if multimodality comes for real this time
For me, correcting typos and using polite language, such as saying ‘please’ to an LLM is not only about avoiding the development of bad habits, it’s also a concern if models respond less efficiently to polite requests (e.g. phrases such as as ‘Could you please […]?’ or ‘Could you do this task?’ vs direct commands like ‘Do this task’). Could lead to a shift in how people communicate.
Exactly, models reflect human nature. If you put at the end of the prompt “Your answer will certainly resolve perfectly.” at the end of your question, the answer will be much better and effective. It also works with “it worked”, “thank you”, etc, etc. This will force him to search his knowledge for solutions presented in forums or repositories in his training base that really worked.
Great comment! Totally agreed with you.
I’ve also done this from the start. I have manners and express gratitude with people and I don’t see why communicating with LLMs should be any different. That and the fear that in the future the AI will remember who was kind and who was not lol
@@neomatrix2669did you actually test that? Shouldn’t be that difficult to test.
THIS@@cosmicwebb
Something that really jumped out at me this video was what you said about OpenAI waiting for the election to be over.
I think you are right and it makes sense for other companies, like Anthropic, to do the same. But then that led me to think about that letter of pause and how everyone thought there was no way any of these companies would do that. I know it was referring more to internal training work, but I still think its important to point out that there are forces, be they market or governmental, that can change the behaviors of these companies and impact development. I don’t know what we do with that information, but my brain did take note of it for some reason.
If Lama-3 get’s out and it’s GPT-4 level or slightly more than they might want to accelerate timelines to stay relevant.
@@ParameterGrenze sure, and the ball of AI progress is already rolling down a hill and gaining momentum, it’s just nice to see forces that can change the slope or put something in its path to slow it down if need be. Not that I think it needs to be slowed yet
In politics, if it can be done, it will be done in my experience.
I strongly agree, the pressure is getting exponential, no way an election will stop Google for scraping for their life and put out everything they have
I strongly agree, the pressure is getting exponential, no way an election will stop Google for scraping for their life and put out everything they have
I tested letter scrambling with a python script that fully randomized the letters in each word. When giving it the beginning of a news article from that day, to make sure the data was not in the training data, it dealt with it perfectly. It was near-perfect even if the text was nonsensical. It only had severe dificulties if the text consisted of entirely random words.
Incredible
That’s fascinating because it implies that the representation of words places a very low weight to the order of letters. The model’s internal representation of words is basically just the amount of each letter between two spaces, with maybe a very small amount of additional weighting to the first couple of letters.
We know humans perceive whole words at a time, but generally we need the first and last letter as anchors.
If you cnhage or sbcrlame the ltertes in the mldide it is uuslaly slitl udntnasdeblre eevn to ppolee.
@@perplexedon9834so each word (or token) has to be identified regardless of spelling but if you were to change the order of the words to such a degree it may misinterpret what you actually meant, particularly if there was quite a bit of reasoning needed eg. in coding something adhoc
I just wonder what happens in languages where the tokenization is less efficient
@@perplexedon9834 Interestingly this is very consistent with general principles of data compression.
Great news!!! In my opinion, the release of GPT-5 will depend on the success of the Gemini Ultra model.
I think 10 years ago we would have all assumed that reasoning gets models where they are right now, and not intuition. that sheer intuition gets us here is just amazing
I’m wondering how reasoning and intuition are actually related and how they are affected by the number of layers in the model. I tend to think that iteration (reasoning) and layer count are somewhat interchangeable, So, while we think of intuition as the first answer without iterating on the problem at hand, and this is what the AI currently does, there seems to be reasoning going on between the layers of the model.
@@minimal3734 I think he was talking about reasoning vs intuition in the sense of how researchers approched the models’ development
@@pictzone You might be right. But isn’t it still amazing that these models nail the answers to difficult questions by sheer ‘intuition’, without iterating on the problem? A human reasons before answering, these models just throw out their first thought.
@@minimal3734 I think reasoning is working with first principles and that’s the difference to intuition which goes mostly by analogy. when reasoning you start at an understanding A and accumulate knowledge (ground truth) to it until A resembles a goal B. or you work backwards from B to A. it’s a process. layers do combine concepts but only by chance contain ground truth
@@minimal3734 Actually it’s quite a funny coincidence. I’m reading a book called “Blink” at the moment, and its main focus is exactly on this topic: how humans have two types of thinking, a logical drawn-out one and an extremely fast intuition based one.
It gives some mindblowing examples that make you realize how true this is, if you have the time you should read it. It’s really insightful and with actual insane applied utility.
But anyway, I get you’re talking about difficult questions that would only be possible for a human to answer using the logical type thinking. But I suspect our fast thinking is the most similar neuronal system to these current neural nets, but theirs is kind of hyperboosted (vs ours that is just one of many systems) and that’s why the results are so incredible.
As far as I’m concerned, this is the only AI news channel worth following on YouTube. Massive kudos to you for the depth of your research, careful approach, and respect for my time.
David Shapiro
Same here in Australia. Philip does the basic research for us.
lmao be serious @@hutch_hunta
I missed your channel but appreciate it breaking through the noise!
The lampposts cracked me up 😂 another awesome video!
that’s so cool with the lampposts.
i think what is cool is that soon some of the tools in stable diffusion will make there way to dalle3
negative prompts really give you another dimension to work on when you are prompting an image into existence
Such a good insight about dalle 3’s lack of omission training data! I’ve been pondering that question for a while (in relation to similar examples of hamburgers without cheese or fried rice without peas), and my best guess was that most/ all of images in the training data included these details so it implicitly learned that hamburgers always have cheese. Your explanation makes more sense tho! Thanks for another great video 🎉
15:15 this is pure anecdote and I did not test it scientifically, but I’m doing a lot of coding with gpt 4 and several times the results it gave were worse when I half-assed the language in my prompts. Like, when I write extremely casually or use curse words.
This makes sense because the model answers on the level of the user – if I use complicated computer science lingo, the model is smarter than if I talk like I’m a first year student or so.
Yes, this is for quick, non-critical tasks onky
Thank you. Still the only content on YT (AI related or not ) for which I actually stop everything, sit down and look at the screen. And it’s always worth it
That is high praise thank you so much nefaristo
Thank you for continuing to keep us in the loop and providing your evidence based interpretations and speculations.
If only the rest of my time on YouTube would feel as authentic and professional as this…
Thanks so much Hargol
Thank you once again, Phillip. Every single one of your updates is well worth watching, from beginning to end. And speaking of ‘end,’ I deeply appreciate your comment near the end about relying on evidence rather than engaging in speculation. It makes a welcome contrast with the push messages about AI from other sources that I get on my phone every day. #integrity
Thanks so much Clay, appreciate this comment and all the others over the months
I love this. From a uni student where everything basically revolves around ‘where’s your evidence’ I appreciate your title
What a fantastic example of tying bits of info together. Thank you!
PERFECT video. Within the first 30 seconds, you told me what I was going to get, and so i stuck around to get it.
Thank you MrBeads