Altman has agreement to return, while most of the board that fired him is out.
Meanwhile, some new details emerged about the days leading up to Altman's firing. "In the weeks leading up to his shocking ouster from OpenAI, Sam Altman was actively working to raise billions from some of the world's largest investors for a new chip venture," Bloomberg reported. Altman reportedly was traveling in the Middle East to raise money for "an AI-focused chip company" that would compete against Nvidia.
As Bloomberg wrote, "The board and Altman had differences of opinion on AI safety, the speed of development of the technology and the commercialization of the company, according to a person familiar with the matter. Altman's ambitions and side ventures added complexity to an already strained relationship with the board."
"According to people familiar with the board's thinking, members had grown so untrusting of Altman that they felt it necessary to double-check nearly everything he told them," the WSJ report said. The sources said it wasn't a single incident that led to the firing, "but a consistent, slow erosion of trust over time that made them increasingly uneasy," the WSJ article said. "Also complicating matters were Altman's mounting list of outside AI-related ventures, which raised questions for the board about how OpenAI's technology or intellectual property could be used."
Because "AI" hype is what the venture capitalists are feeding to the financial and tech press theses days and Sam is the venture capitalists biggest "AI" star because he's a good snake oil salesman.
While not inaccurate, that is extremely reductive. The rapid improvement of AI at the transformer level is currently one of the most interesting things happening across many fields including arts and sciences, that also has the widest deviation between potential good and potential harm. OpenAI and its complex governance model are directly at the center of that growth and embroiled in one of the most fascinating governance struggles in recent history.
This drama when combined with how disruptive this technology is likely to be across a wide range of markets affecting the world’s economies makes this interesting and also has the added benefit of being a news departure from the bombings and other terrible stuff going on around the world. Much more fun for popcorn and chat than wars and such.
As a developer, comments that talk about how ChatGPT is changing the development game confuse the hell out of me. What are you people doing that ChatGPT makes your workflow massively more productive?
It gets documentation/help wrong or straight-up makes shit up
Same thing with having it generate actual code
If "generating code I'd normally copy/paste" is such a game changer, your architecture/design needs a rework
Yes, even for tests (seriously, we've had ways to pass arrays of inputs into tests for years, having it copy/paste the same test a hundred times with different values is fucking atrocious)
Code "assistant" suggestions have been fucking horrid from my experience with them (and I end up disabling it every time I give it a try)
When using any new language or framework I can get up and running very quickly.
Used to take time to read the intro docs and then start digging around trying to find the features I need. Now I can straight ask it how to do certain things, what is supported and the best practises.
If I see a block of code I don't understand I can ask it to explain and it will write out line by line what it's doing. No more looking for articles with similar constructs or patterns.
It's amazing at breaking down complex SQL.
Many tedious refactoring tasks can be done by it.
Creating mappers between classes is very good because it can easily pickup matching properties through context if types and names don't match.
Generating class from a db table and vice versa.
If you have a specific problem to solve rather than googling around for other solutions you can ask it for existing methods. This can save days or more of discovery and trial and error.
It's really good generating test cases based on a method.
Recently I implemented a C# IDictionary with change tracking built in. I pasted the code in, it analysed it and pointed out a bug then wrote all the tests for the change tracking.
It did better than I thought it would. Covering lots of chains of actions. Which again found a bug.
It's fairly good at optimising code as well.
As for the mistakes you should be able to spot them and ask it to correct. If it does something invalid tell it that and it will correct.
You have to treat it like a conversation not just ask it questions.
Like Google you have to learn how to use it correctly.
We also have bing enterprise which uses search results and sources its answer. So I can look at the actual web result and read through.
The hallucination thing is basically a meme at this point by people that haven't really used it properly.
When I google an issue I quickly get a list of possible solutions with other developers commenting on them with corrections. People can often upvote and downvote answers to indicate if they work or not and if they stop working.
With ai I get a single source of information without the equivalent to peer review. The answer may be out of date and it may misunderstand my request. It may also make the same mistake I am making that I would have caught with a quick googling.
The ai may be able to make boilerplate code occasionally without too much rework, but boilerplate code is not that hard to make already.
The AI is massively more expensive than a search engine and I have not seen any indication that will change soon. This is the biggest problem in my mind. I don't ever expect to have to pay for google. I expect in the future the ai will need to be paid for somehow and I have a feeling they will have to charge too much to justify the use of AI for software development work.
AI has plenty of good uses, but I do not believe software development is the winner. Block chain for instance was massively useful for git repositories, but not useful for many of the crazy things companies attempted to use it for.
If you use bing search AI it sources its answers. It basically does what you would do when looking through sources and at ratings. But when you find the info you want you can click the link it used to generate it.
Right now AI like that is heavily subsidized by investors. My concern with AIs feasibility is that training is so expensive that it won't be able to stay free. Remember we can only stop ai training if the AI topic is no longer developing. Also if the AI can source its answer with a link, did it provide me with a new service that is better than a search engine?
As a newer developer is has been amazing for me and alot of experienced developers also recognize how much benefit it provides so im honestly confused by your standpoint.
Failing to understand why does not make you correct by ignoring it.
Learning how to use AI tools is another meta-skill just like learning how to use a search engine such as Google. The latter is widely accepted as a must-know for software developers.
While large language models and similar "AI" technologies are very overhyped, they are already plenty usable for things like deepfakes which if left unchecked have significant potential to be weaponised and destabilize societies.
OpenAI is a non-profit that's behind those machine learning models and practical applications like ChatGPT. In principle it should govern development so that it's safe and responsible. There are many allegations that Sam Altman became focused on profit betraying non-profit mission.
While OpenAI is not technically controlled by commercial entities (it has 49% stake by Microsoft) it's entirely dependent on them for funding which likely led to being strong-armed to have Altman regain control.