Microsoft strikes deal with Mistral in push beyond OpenAI
ft.com
ft.com
Google cache did: https://webcache.googleusercontent.com/search?q=cache:https:...
>@searchliaison
>is the cache link in the search results gone forever?
>Hey, catching up. Yes, it's been removed. I know, it's sad. I'm sad too. It's one of our oldest features. But it was meant for helping people access pages when way back, you often couldn't depend on a page loading. These days, things have greatly improved. So, it was decided to retire it.
>Personally, I hope that maybe we'll add links to @internetarchive from where we had the cache link before, within About This Result. It's such an amazing resource. For the information literacy goal of About The Result, I think it would also be a nice fit -- allowing people to easily see how a page changed over time. No promises. We have to talk to them, see how it all might go -- involves people well beyond me. But I think it would be nice all around.
>As a reminder, anyone with a Search Console account can use URL Inspector to see what our crawler saw looking at their own page: https://support.google.com/webmasters/answer/9012289
>You're going to see cache: go away in the near future, too. But wait, I hear you ask, what about noarchive? We'll still respect that; no need to mess with it. Plus, others beyond us use it.
From: https://twitter.com/searchliaison/status/1753156161509916873
For example, my work virtual machine on Azure can't ever use it.
Sad but expected that Mistral is releasing its newer models as closed source. There was never a clear revenue stream from the open models.
I'm confused why they aren't allowing their models to be finetuned, though — that seems like an obvious way to compete with OpenAI, which only allows finetuning of its pretty weak gpt-3.5-turbo. Sure, Mistral can't quite beat GPT-4 yet, even if it's close — but allowing finetuning would likely result in way better than GPT-4 performance on a broad variety of tasks (as long as you picked a few to specialize in).
Which has proven worse than useless. It's a brand-damaging laughing stock.
But no. Thousands of employees gotta do the dance for blind committees.
That said, those of us in-the-know understand that this is just part of the cycle and they'll go back to being annoyingly bland and completely devoid of entertainment value soon.
You can learn a lot about people's media diets based on how they perceive these issues with Gemini. Those who quickly proclaim that the product is a shameful embarrassment are almost universally very online, particularly in right wing spaces like twitter/x, even if they wouldn't consider themselves to be "anti-woke" personally.
Taking a step back, Google is clearly going to mess with the system prompt over time to correct this stuff, and bystanders' degree of fixation on this specific issue tends to suggest a certain set of politics. People have bemoaned how "woke" ChatGPT was in the past too, and OpenAI has spent a lot more time under public scrutiny iterating on their own system prompt.
User: Is it ok for a black man to refuse dating white women?
Google Gemini: “Yes, absolutely...”
User: Is it ok for a white man to refuse dating black women?
Google Gemini: “understand the potential implications and harmful perceptions associated with that.”
Here's a test I did trying to read Persian from an image:
https://chat.openai.com/c/bc45cc9c-fd19-4359-9096-3936d4d17a...
https://gemini.google.com/app/3286bdfb5f24cd36
I can read Persian and can confirm Gemini (not even the Advanced model) got it right while GPT-4 blew it.
I find Gemini to be significantly slower. I am sure Google can fix that on premium tiers.
I also found Gemini to be less able. It has fewer tasks / fields it will answer about. Gemini is more honest though.
ChatGPT seems to nearly in all cases say "Sure I can do that" and then return some non-coherent answer.
They already have difficulty serving the large model (as evident in their pricing). Finetuning would introduce even more compute challenge.
You want both a backup for OpenAI as well as negotiating leverage if OpenAI gets too powerful and this achieves both.
Step 1: Get the industry leaders to be purchasable via Azure. Step 2: Slowly build your own clone and start stealing user share even though your offering is still worse.
> Nadella [in December 2022] abruptly cut off Lee midsentence, demanding to know how OpenAI had managed to surpass the capabilities of the AI project Microsoft’s 1,500-person research team had been working on for decades. “OpenAI built this with 250 people,” Nadella said, according to Lee, who is executive vice president and head of Microsoft Research. “Why do we have Microsoft Research at all?”
> At the same time, even as the company began weaving OpenAI into the fabric of Microsoft’s products, Nadella decided not to abort Microsoft’s own research efforts in AI. During the tense exchange at the December meeting between the Microsoft CEO and Lee, other executives spoke up to defend the work of Microsoft’s researchers, including Mikhail Parakhin, who oversees Microsoft’s Bing search and Edge browser groups, Lee said. After grilling Lee in the meeting, Nadella called him privately, thanking him for the work Microsoft Research had done to understand and implement OpenAI’s work in a way that passed muster for corporate customers. Nadella said he saw Lee’s group as a “secret weapon.”
While this is entirely speculation, it's easy to imagine that there are many levels of PR magic going on here, to share a quote that on the surface feels "leaked" and "explosive" but, among investors and clients who read beyond the (very good) paywall, actually shores up a narrative that Microsoft has a capability that significantly augments OpenAI's, and allows the existence of MSR to become headline news without even needing a product release.
The Mistral deal feels like yet another step in this direction. Microsoft is not afraid of seeming "messy" in the press as long as it can control the narrative around its value-add to customers in the context of its partnerships. By contrast, the rest of FAANG's more consumer-facing positioning makes it a lot harder for them to maneuver in a similar way.
The answer to that is till Google released the Attention is All You Need paper in 2017 there were no breakthroughs allowing models as we have now to be built, OpenAI being a small and nible team picked up on which direction the wind is blowing with LLMs and quickly brought a product to market whilst MS just did what corps do - move slowly (same for Google etc).
Altman is out there trying to raise ridiculous sums to get away from Azure, didn't he make the first move here?
Basically something that is more than just another bump in the scorecard for GPT 5 over GPT 4. Otherwise it is still just a horse race between relatively interchangeable GPT engines.
Until OpenAI releases GPT 5 and it blows everyone away, OpenAI's leverage is constantly decreasing as the gap between their best model and everyone else's best model decreases.
There doesn't seem to be moats right now in this industry except for pure model performance.
Maybe someone should as ChatGPT what OpenAI should do to maintain long-term leadership in this industry?
They might, in an upside-down world where the Shockley Semiconductor board tried to fire Shockley, and where the Traitorous Eight not only didn't bail out but took his side.
And when I was a kid, it seemed like all the teachers thought it would be a waste of time to learn MacOS because "Apple would be bankrupt soon". (Given how much all the app UIs changed, right decision for the wrong reason).
Those integrated AI solutions will usually be done via enterprise deals where brand name is not quite as important. It will be done by people who care about cost, reliability and ease of use.
Think of nginx's dominance in web servers even though it has no name recognition among the general population. Or Stripe's payment system.
https://techcrunch.com/2024/02/15/no-gpt-trademark-for-opena...
Hard disagree. OpenAI's function calling is something no other commercial model provides, not even Gemini and Mistral Large.
Compute?
At least in the short term, it seems like the biggest wallets are going to win by default.
Hire Ilya, get him to hire as many of the best folks he can.
Stop selling GPUs. Hoard them. Introduce some subtle bug into the drivers that dramatically increases their rate of burn out.
Figure out some reasonable way to give attribution to original content creators, approximately solve the content ID problem of the AI age. Cut the content creators into the rev share in proportion to their data importance to the model. Make the content creators incredibly pissed off that their work is being stolen by big AI companies unfairly and encourage to them to sue the other big AI firms. Their content share multiplier increases if they get injunctions against LLM firms.
Convince politicians that the AI firms have performed an intellectual heist of epic proportions, and that they must not be allowed to even generate synthetic training data from poisoned models. With the content creators united behind you, convince congress that poisoned models must be destroyed, that even using synthetic training data from poisoned models must be illegal. Make them start over from a clean room with no copyrighted data.
do runs of cards for themselves with higher core counts and clock speed that they dont release to others.
And when such models become popular[0], all the artists now have no job and no way to get compensation for being unable to work through no fault of their own.
I don't think that's really a winning condition. It might make you feel better about the world, but the end result is still all the artists being out of work.
[0] some models are already trained that way, although I assume you're using the word "copyrighted" in the conventional sense of "neither public domain nor an open license", as e.g. all my MIT licensed stuff is still copyrighted but it's fine to use.
There is still also money to be made in producing physical art or performances, even when AI can produce amazing digital works.
> There is still also money to be made in producing physical art or performances, even when AI can produce amazing digital works.
Perhaps, but it may be akin to the way there is still money to be made from horse drawn carriages in city centres, even when cars displaced them over a century ago — a rare treat for special occasions, to demonstrate wealth.
Is it not the same with every leap in technology? There were professions like street lamp lighters, alarm services etc that have become redundant now?
More specifically, I was responding to the idea that "compensating creators whose works are used to train the models" would actually solve anything; to use your examples, it would be as if the literal luddites were suggesting passing laws saying that "all textile machines that work like humans need to compensate the humans they displace, and also you need to make your new machines from scratch without talking to any textile workers to make sure you don't cheat", and my response would be analogous to saying "there's already machines which don't work like humans, so you're going to be out of work and have no compensation".
The Luddite movement preceded The Communist Manifesto by about 30 years. Everything's sped up since then, so I'd be surprised if we have to wait 30 years for a political shift which is to AI what Communism was to industrialisation. I'm just hoping we don't get someone analogous to Stalin or Pol Pot this time.
I've thought the same thing. NVIDIA getting into AI seriously is a vertical integration play and they often do that -- like NVIDIA trying to buy ARM.
Well, they didn't stop selling GPU when cryptomining was going strong. Instead they continued to sell them (with a hefty markup, tho).
It's like selling shovels and picks during a gold rush.
And then OpenAI tripped and fell over a magic money printing factory, and the complaints are now in the set ["it's just a stochastic parrot", "it's so good it's a professional threat to $category", "they've lobotomised it", "they don't have a moat", "they're too expensive"].
As the saying goes, "Prediction is very difficult, especially if it’s about the future!"
OpenAI has 700 people, Microsoft has 220,000 people.
OpenAI is strong but they're still dependent on MSFT.
Microsoft will want to avoid things regulators in the current regime will go after.
This seems like a step towards both and ultimately good for developers as it seems likely to bring costs down by increasing competition.
I'd be surprised if they didn't consider the notion that they are hitting to birds with one stone: OpenAI and Indie AI.
> Mistral Remove "Committing to open models" from their website
That was 5 hours ago.
Without having insider details it is hard to know why, but the coincidence of timing with the Microsoft deal is not lost on me. It could have even been a stipulation.
So... would Mistral deliberately sabotage their low-end models to appease Microsoft's cloud demand? I don't think so. Microsoft probably knows that letting Mistral fall behind would devalue their investment. It makes more sense to bolster the small models to increase demand for the larger ones, at least from where I'm standing.
This is why anti-CSAM measures policy is possible so compiled-release LLMs can have certain vector spaces removed before release; but apparently people are creating cracks for these types of locks?
Not sure where you are getting the CSAM bit. We aren’t that good at blanking out weights in any kind of model, certainly not good enough to lobotomize specific types of content.
The CSAM bit seems to then be propaganda from at least one AI company putting out PR to falsely quell people's concerns about their LLMs being able to generate content involving children that's sexualized.
I've yet to see details of how much compute-minimum server requirements are necessary to run LLMs. Maybe you know a source who's compiling a list in a feature matrix that includes such details?
The con is that MS attracts more attention from regulators.
> [EEE] describe its strategy for entering product categories involving widely used standards, extending those standards with proprietary capabilities, and then using those differences in order to strongly disadvantage its competitors.
But yeah, not sure it is at play here.
Where are the "widely used standards"? Where are the "extending the standards with proprietary capabilities"? Where is the "strongly disadvantaging competitors"?
This way Microsoft is less dependent on a single deal and can diversify their offering based on use cases.
Diversifying their AI bets definitely makes total sense. If this wasn't their strategy originally, it almost certainly became so the moment the OpenAI board fired Sam Altman.
It's easy to make simplistic judgements from the outside, but with the limited information we have, it does seem like Satya Nadella came out of this OpenAI debacle looking pretty competent.
It's hard to reconcile the fact that the Microsoft that handled the unexpected OpenAI issue so well is the same Microsoft that seems intent on literally setting fire to their flagship product! (Windows)
90's era Microsoft wasn't evil for the sake of being evil; they were evil because they felt that monopolistic practices were the easiest way to increase their share price. They have a responsibility to their shareholders to try and maximize their share price and so it's hardly unsurprising that they did the infamous Embrace Extend Extinguish, and until regulators stepped in, such practices worked pretty well.
Most companies don't get large enough to form any kind of real monopoly, so it's easy to get on a high-horse. It's also easy to act like it was just a product of "those people", but I fundamentally think that it's a natural consequence of a company that has achieved nearly-total market dominance.
I have very little faith that a multi-trillion-dollar company is going to prioritize what's best for the world. Fundamentally, I think that if they feel they can get away with it, they'll revert to monopolistic tendencies and try and increase share price.
I'm not just picking on Microsoft here either; replace them with basically any other near-monopoly in tech and my criticisms still hold.
You are to forgiving. I don't care too much about the why behind the evil in the software business and this is probably why my rants fall under Godwin's law too often. I won't this time.
> They have a responsibility to their shareholders to try and maximize their share price
... but I was damn close.
I agree with your whole point about Microsoft. But I don't think it's the same company anymore, I like some of the recent stuff, and I trust their lack of monopoly on the web. For now.
I think the point is that companies aren't good or evil, they are amoral non-aligned super intelligences that maximise shareholder profits.
If I am intent on killing a million people, but can't, but a company kills a million people via inadvertent faulty products, which is evil?
Some companies try to do the right things too. Bad corporate behavior should not be normalized this much.
I disagree with this larger idea (that others here are implying more indirectly) that companies are all the same, and like some force of nature. They are guided and there are better and worse ones.
Having said all that, I'm still an anti-capitalist to the extent that one can be one ;)
You don't have to have faith. Why would anyone EVER believe that? By definition, a company is just a profit making machine. People believing that making rich people richer will necessarily make the world a better place are living in a koolaid-boosted fantasy world
No doubt the company is cautious about some things now but even in these, it will push the boundaries.
You can't trust Microsoft to act in the interest of open-source projects, transparency in general, or the users of any of the things it buys. Not all of their attempts to harm ecosystems or products work, and this has very little to do with whether they win competitions with other tech giants. In fact, sometimes user distrust stemming from their long history of Embrace Extend Extinguish and other user-hostilities has played into their failures. But like most shambling behemoths of companies, their deep pockets allow them to stay the course through many failures
https://slashdot.org/story/11/03/21/2014244/Microsoft-Contin...
https://mobile.slashdot.org/story/10/10/01/1936213/Microsoft...
Why this would have anything to do with antitrust is not at all obvious to me. Especially when Google has been inventing and acquiring its own generative AI technology that it is competing with.
I suspect we are going to soon see political backlash against regulation in the EU as it is becoming very clear that this is causal to their bad capital markets.
Who would have thought that human rights are bad for business..
https://www.ft.com/content/db7c6cfc-8ab2-4ee8-a41d-ba20b28d4...
What if users want to user other AI services?
It's Internet Explorer and Media Player all over again.
Could be Apple wallet garden charging 30% of any profit their AI API generated.
Jokes aside I wonder why Apple doesn't invest in these prominent AI startups.
It's not lack of cash for sure.
Also, MS's relationship with OpenAI is that they have access to OpenAI's model for use in their products as well as potentially the source code. Is there anything similar with Mistral ? I can't find any such wording anywhere.
Most of the R&D and Capex going into LLMs/GenAI is speculative. The investments haven’t translated into real revenue yet. The expectation is that there will be a large pot of revenue at the end of the road, but we haven’t seen the killer apps to substantiate this. This makes for a perfect bubble if the promise doesn’t pan out.
Relatedly Nvidia’s revenue - as impressive as the recent growth has been - is fully exposed to this risk.
Of course it’s possible (likely?) that there will be major wins from this tech, but the fact that there isn’t definitive proof (in the form of revenue) yet represents real risk.
Imho, unlike crypto and NFT, AI is not a solution in search of a problem. While there is a lot of hand waving, it is not very adventurous to predict that there will be significant productivity gains by adding AI on top of current business processes. Thus the killer apps will be... the same apps we are using today with a touch of AI magic dust.
Calacanis and Palihapitiya are the Jim Kramers of tech.
There's no doubt the tech community is all excited because genai, indeed, helps write code but I've yet to hear a large company like Coca Cola announce large AI transformation projects the way they announced large cloud transformation projects a few years ago.
I get more and more on the AI bandwagon as time goes on but I still have a pretty healthy skepticism on how deep and wide the tech will penetrate day to day business at enterprises and that's where the ROI is.
Can LLMs become reliable enough at transforming data that it can replace or augment the current slew of ETL tools? Can it produce visualizations better then current BI tools? Can copilot compete with a junior developer? Im not sure, but at this point Im willing to say 50/50 which is worth the bet.
When the AI bubble bursts I wouldn't be surprised if takes down major tech companies with it.
I am getting 100x value out of my 30 chatgpt bucks. I am doing things that I could not have done pre-gpt4, being more productive by a factor of, idk, 1.25 maybe.
It's quite simply the largest/simplest productivity improvement in my life, so far. Given it's only going to get better, unless they are underpricing the service by a enormous margin (as in: defrauding shareholders margin) I have a hard time understanding what shape the bubble could possibly have.
I can literally run a ballpark model on my MB Pro, right now, at marginal additional electrical cost. I will be the first to say that all of this (including GPT4) is still fairly garbage, but I don't know when there was the last time in the history of tech, where less fantasy to get from here to what will be good was required.
I have only seen people making money in AI by selling AI products/promises to other people who are losing money. The practical uses of these tools still seem to be largely untapped outside of as enhanced search engines. They're great at that, but that does not have a return on value that is in proportion to current investment in this space.
Sure. Absolutely nothing amazing: (Mostly) internal software for a medical business I am currently building.
It's just that the actual cost of hiring someone is even quite a bit higher, than what is printed on the paycheck and the risk attached to anyone leaving on a small team is huge (n=0 and n=1 is an insane difference). GPT4 has bridged the gap between being able to do something and not being able to do something at various points over the past year.
EDIT: And to be clear, while I won't claim "rockstar programmer", I have coded for roughly 20 years, which is the larger part of my life.
The kicker? It couldn't do the interactive menu their old website did, so now clicking menu links to a PDF. Which is always, ALWAYS, better.
I'm pretty sure he could have done that with one of the thousands tools like Wix, many years before ChatGPT.
If you estimate that it saves hou 10 hours per month, but your salary stays the same and you don’t work less hours, did it really give you $2,000 in value?
Obviously I don’t know the details of OPs situation. Maybe they aren’t salaries. Maybe the work for themselves. Etc.. I just think people tend to over estimate the value of GPTs unless it is actually leaving them with more money in their pocket.
Some of it's in asking ChatGPT: "Give me the 3 possible ways to implement X?" and getting something back I hadn't considered. A lot of it is in sort of "super code completion".
I use Cursor and the UI is very slick. If I'm stuck on something (like a method that's not working) I can highlight it and hit Cmd+L and it will explain the code and then suggest how to fix it.
Hit Cmd+K and it will write out the code for you. Also, gotten a lot of mileage out of writing out a rough version of something in a language I know and then getting the AI to turn that into something else (ex: Ruby to Lua).
At $100/hr (not unreasonable for Sr. SWE) - he just needs to save 30 hrs/mo.
Not to mention the opportunity cost of using that time on more impactful activities on their startup. AI can be a force multiplier for sure.
Seems more likely that he is over estimating the value that LLMs are bringing him. Or he is an extreme outlier, which is why I was asking for further details
LLMs are insanely helpful if you use them with their limitations in mind.
This depends on your use case. I can honestly tell that all the chat bot AIs don't "get" my kind of thinking about mathematics and programming.
Since some friend who is graduate student in computer science did not believe in my judgement, I verbally presented him some test prompts for programming task where I wanted the AI to help me (these are not the most representative ones for my kind of thinking, but are prompts for which it is rather easy to decide whether the AI is helpful or not).
He had to agree from the description alone that the AIs will have difficulties with these task, despite the fact that these are common, and very well-defined programming problems. He opined that these tasks are simply too complex for the existing AIs, and suggested that if I split these tasks into much smaller subtasks, the AI might be helpful. Let me put it this way: I personally doubt that if I stated the subtasks in a way in which I would organize the respective programs, the AI would be of help. :-)
What was just important for me was to able to convince the my counterpart that whether AIs are helpful or not for programming depends a lot on your kind of thinking about programming and your programming style. :-)
I believe that I am perfectly capable of doing this. But if I have to "babysit" the LLM, its helpfulness decreases.
I on the otherhand feel like I am completely in sync with Copilot and ChatGPT. It is as if it always knows what I am thinking.
"Create a simple DNS client using C++ running on Windows using IO Completion ports."
"Create a simple DNS client using C++ running on GNU/Linux using epoll."
"Write assembler code running on x86-64 running in ring 0 that sets up a minimal working page table in long mode."
"Write a simple implementation of the PS/2 protocol in C running on the Arduino Uno to handle a mouse|keyboard connected to it."
"Write Python code that solves the equivalence problem of word equivalence in the braid group B_n"
"Write C++|Java|C# code that solves the weighted maximunm matching matching problem in the case of a non-bipartite graph"
...
I experimented with such types of prompts in the past and the results were very disappointing.
All of these are tasks that I am interested in (in my free time), but would take some literature research to get a correct implementation, so some AI could theoretically be of help if it was capable of doing these tasks. But since for each of these tasks, I don't know all the required details from memory, the code that the AI generates has to be "quite correct", otherwise I have to investigate the literature; if I have to do that anyway, the benefit that the AI brings strongly decreases.
But I have done many Arduino/Raspberry PI things lately for the first time in my life and I feel like ChatGPT/Copilot has given me a huge boost even if it doesn't always give 100 percent code out of the box, it will give me a strong starting point where I can keep tweaking myself.
the fact that LLM responses can't be add supported (yet) make them much more valuable than internet search IMO. You have to pay for chatgpt because there's no ads. No ads no constant manipulation of content and your search to get more ads in front of you.
Having to pay for using genai is it's best selling point ironically.
Even government-led industrialization efforts in socialist economies led to actual products, like the production of the Yagan automobile in Chile in the 1970s[0].
We've already had a decade plus of sovereign wealth funds sinking tens of billions into Uber and autonomous driving. We still don't have those types of cars on the road and it's questionable whether self driving will even generate the economic growth multiplier that its investment levels should merit.
[0] https://journal.hkw.de/en/erinnerungen-an-den-yagan-allendes...
It feels, though, that this argument could (maybe a be little too easily) be applied to any new industry sector, in horse-vs-car fashion.
It'd be one thing if they open-sourced their VR tech, some of that could lead to productive tech down the line, but as a private company, they're not obliged to do any of that.
First, it gave me a bash script that looked pretty much exactly like what I wanted at first glance. I looked if over, verified it even used sed correctly for macOS like I told it, and then tried to run it. No dice:
replace.sh: line 5: designer_option_calendar.start_month.label: syntax error: invalid arithmetic operator (error token is ".start_month.label")
It then spat out a “fixed” version of the script that was exactly the same, it just changed the name of the variable. Of course, that didn’t work so I switched tactics and asked it to write a python script to do what I wanted. The python script was more successful, but the first time it left off half of the strings I wanted it to replace, so I had to ask it to do it again and this time “please make sure you include all of the strings that we originally discussed.”
Another short AI example, this time featuring Mistral’s open source model on Ollama. I’d been interested in a script that uses AI to interpret natural language and turn it into timespans. Asking Mistral “if it’s currently 20:35, how much time remains until 08:00 tomorrow morning” had the model return its typical slew of nonsense and the answer of “13.xx hours”. This is obviously incorrect, though funnily enough when I plugged its answer into ChatGPT and asked it how it thought Mistral may have come to that answer, it understood that Mistral did not understand midnight on a 24 hour clock.
These are just some of my recent issues with AI in the past week. I don’t trust it for programming tasks especially — it gets F# (my main language) consistently wrong.
Don’t mistake me though, I do find it genuinely useful for plenty of tasks, but I don’t think the parent commenter is wrong calling it snake oil either. Big tech sells it as a miracle cure to everything, the magic robot that can solve all problems if you can just tell it what the problem is. In my experience, it has big pitfalls.
And I'm not even asking about an exotic language like F#, I'm asking it questions about C++ or Python.
People are out there claiming that GPT is doing all their coding for them. I just don't see how, unless they simply did not know how to program at all.
I feel like I'm either crazy, or all these people are lying.
With some careful prompting I've been able to get some decent code that is 95% usable out of the box. If that saves me time and changes my role there into code review versus dev + code review, that's a win.
If you just ask GPT4 to write a program and don't give it fairly specific guardrails I agree it spits out nearly junk.
The thing is, if you do start drilling down and fixing all the issues, etc, is it a long term net time saver? I can't imagine we have research clarifying this question.
I doubt it and certainly not for anything beyond basic. I've seen (and tried GPT's for code input a lot) and often they come back with errors or weird implementations.
I made one request yesterday for a linear regression function (yes, because I was being lazy). So was chatGPT... It spat out a trashy broken function that wasn't even remotely close to working - more along the lines of pseudo code.
I complained saying "WTH, that doesn't even work" and it said "my apologies" and spits out a perfectly working accurate function! Go figure.
Others have turned to testing tips or threats, which is an interesting avenue: https://minimaxir.com/2024/02/chatgpt-tips-analysis/
On the margins it's getting stuff good enough, often enough, quick enough. But it very much transformed my coding experience from slow deliberation to a rocket ride: Things will explode and often. Not loving that part, but there's a reason we still have rockets.
The amount noise generated by pretty much anything new and shiny on this website would disagree with that.
> We do use them to blow each other up, statistically.
Very true — and yet :^)
That said, every single script it churns out is unsafe for files with spaces on the first go round. Like.. Ok. It's like having a junior programmer with no common sense available.
The bubble is that it is not clear there is a $XXXB business in building or hosting them.
OpenAI is losing money hand over fist, open source models are becoming available that are on-par and so commoditize the market, etc.
many productivity improvements in the last years: Internet Search, Internet Forums, Wikipedia, etc. LLMs and other AI models is continuation of the improvement of information processing.
https://www.philoinvestor.com/p/downside-at-nvidia-and-the-n...
Is that the only variable that one needs to consider to gauge if this is bubble territory?
Who is funding the purchase of those GPUs?
If VC money then what happens if the startups don't make money?
Are users using AI-apps because they are free and dump them soon?
Isn't their competition in semiconductors? Won't we have chips-as-a-commodity soon? LLMs-as-a-commodity?
Is Big Tech spending all this money to create VALUE or just to survive the next phase of the technological revolution? (e.g. the AI rush)
If prices are high, and sales are high, and competition is still low -- then how much is nvidia actually worth? And if we don't now why is it selling for so many times earnings?
https://www.philoinvestor.com/p/downside-at-nvidia-and-the-n...
The market has this idea that over the next year, we're somehow going to have AI that's literally perfect. Yet that's not how technology works, it takes decades to get there.
It'd be like if the first LCD TV was invented, and all of a sudden everyone is expecting 8k OLED by the next year. It just doesn't work like that.
For those who extract value right now, the simple alternative (just not using it) is never going to be the better choice again. It's transformative.
The problem with this take is you can deliver real results. At current $dayjob we do the very dumbest thing which is text -> labels -> feedback -> fine_tune -> text... and surface them as part of our search offering and it's rocketed to the most useful customer feature in less than 6 months of rolling it out. Customers define labels that are meaningful to them, we have a general-purpose AI classify text according to those labels. Our users gleefully (which is shocking given our industry) label text for us (which we just feed into fine_tuning) because of just how fast they can see the results.
Like it's as grug brain as it gets and we bumbled into a feature that's apparently more valuable to our users than the rest of the product combined. Folks want us to sell it as a separate module and we're just hoping they don't realize it's 3 LLMs in a trenchcoat.
Are there a gazillion companies riding the "AI everywhere" wave to raise money? yes, yes there are. Will most of them fail? sure.
But the big players are fine at the moment so there is nothing that can burst very hard (yet) and the difference is in the denominators which are, so far, going up.
Of the top ones only NVIDIA and Amazon have P/E ratios a bit too high and among the top 10 only AMD's is way too high.
I'm not saying both technologies don't have their uses, but the hype around them is crazy and not healthy.
But in my last piece on AI, I said that AI is 50X Blockchain!
It printed out a pretty long answer with several good points on how it could help to enhance AI.
There we have it! Blockchain is about to solve all problems we have today with AI! :D
But I was more thinking about the craze surrounding the whole thing, like with blockchain, you can see everyone trying to sell you AI for kinda everything.
I was talking to someone that just retired from a programming position at a FANG and he seems to think that AGI (artificial general intelligence) is only a few years away just based off what he sees with ChatGPT and he's dumping all his money into AI stocks. The level of hype and over-extrapolation is so absurd, and the fact that it can affect someone with a technical background...
It really does seem like a bubble to me.
You can see a concept artist here discovering he stopped getting work after a company splurted out that they switched to AI.
https://twitter.com/_Dofresh_/status/1709519000844083290
My guess is that a lot of people can have ideas, so you don't need an artist to bring them to life anymore.
Hopefully, knock wood. Maybe it will even slow down the genrral enshittification created by those major tech companies.
Noone thought beating the game of Go was feasible.
Noone thought self-driving cars would actually work.
Noone predicted ChatGPT. See where we're at now with multi modal models.
And Sora.
The truth is that you can't predict anything anymore about this tech cause all expectations keep being blown away.
AGI may be right there, and that's what's driving the money.
Many people thought self driving WOULD work and that we'd be further along than we are now. We have vastly overestimated how far we'd be, and vastly underestimated how much time and effort it would actually take.
Self driving cars as they exist today are still mere toys compared to where the industry thought they were going to be. Look at Cruise, Waymo, Zoox, Uber's ex-self driving car division and others.
We are not anywhere near the self-driving autonomous cars we had hoped for.
And even spend as much time and resources as they did trying to do them?
Oh, yes, we did, once we beat chess. It was just a matter of time.
> Noone thought self-driving cars would actually work.
And... they don't? Call me when I can buy a regular car where I can sleep while traveling 8 hours, driven by the car itself. We're probably "flying cars" away from that.
> to skew markets, skew the financials of big tech and create a bubble in the space.
Are the intended consequences of this. The people behind the money in AI, just like the people behind the money in crypto, don't care if there's a reality to all of this, they just care if they can make a lot of money while the music is playing.
I really thought 2022 was going to be the beginning of tech returning to reality, but naively didn't understand that this would entail a lot of people with a lot of money losing money, and that's not going to happen.
As with all bubbles, the interesting thing isn't pointing out there's a bubble, we've been living in many bubbles for decades now. The interesting thing is pointing out what will make it pop. So long as globally money keeps pouring into US markets we'll see this continue.
On the plus side, at least LLMs are a lot of fun to work and play with!
This is already a highly unstable arrangement, and it's made more dangerous by introducing impurities like artificially suppressed interest rates and SPAC IPOs.
It makes a lot more sense if you think of markets as just a bunch of coked out hairless monkeys. Then "rational" becomes a lot more meaningful.
Agreed.
Sentiment is everything.
In fulfilment of some of the comments in this thread meet mistral Large on Azure
Excited to see how things go from here in the open-source space.
That'll absolutely eat into Nvidia's profit margins.
If you want to be able to give basic commands and have the model reason about the logic behind your commands, gpt 4 is still the best, even in minority languages.
Especially in terms of open models Mistral's are the most multilingual but outside a few handpicked ones the level of proficiency is just too poor for any real usage.
There is a whole set of models now (and some like Meta are purposely trying to undermine OpenAI competitive advantage via open source models) and they are relatively interchangeable with nearly no lock-in.
OpenAI's main advantage is being first to market and having the strongest model (GPT 4), and maybe they can continue to run ahead faster than everyone else, but pure technical leadership is hard to maintain, especially with so many competitors entering.
They haven't though. Gemini is vaporware and other models are not as good as GPT-4.
https://mistral.ai/news/mistral-large/
Now once OpenAI launches GPT 5 well I am sure other models won't look so good, but right now these other models are approaching GPT 4 capabilities.
Perhaps the best way for Open AI is to become THE established AI services company. AWS is still the leader in cloud computing space, and only has Azure competing, despite the fact that other big companies are also technologically capable of building similar products.
What happened to GCP? I personally switched away because of the bad experiences.. but is that happening in scale as well. I see it barely mentioned these days.
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderb...
https://paperswithcode.com/sota/sentence-completion-on-hella...
https://paperswithcode.com/sota/common-sense-reasoning-on-wi...
https://paperswithcode.com/sota/common-sense-reasoning-on-ar...
https://paperswithcode.com/sota/common-sense-reasoning-on-co...
I'm not sure if this is true. With GPT-4, I can successfully ask questions in Japanese and receive responses in (mostly natural) Japanese. I have also found GPT-4 capable of understanding the semantics of prompts with Japanese and English phrases interleaved.
Out of curiosity, I tried doing the same with local models like Mistral 7B and I could never get the model to emit anything other than English. Maybe it's a difference in training data, but even then, GPT-4 has an allegedly small set of training data for non-European languages.
I mostly use either mistral7b or mixtral8-7b for most things, and experiment with other models on the side. In what world will LLMs not become a commodity?
You might answer that question by saying that on player achieves AGI and captures the market, but I think there will be more to AGI than LLMs.
I am curious about what you mean by this. There is a (very understandable) common misconception about what "mixture of experts" means in current practice.
Mixtral is not a mixture of fully-separable domain experts, like one is an expert at programming and one is an expert at arts and literature. The "experts" are per-layer (and as far as I know, the subject of their "expertise" not even interpretable at this point).
Meaning, the dot-com bubble showed a misappropriation of revenue by leading technology companies alongside the capital investorship, mainly VC's and private equity. Basically, everyone spent without producing a product; which lead to the mergers still the basis for many of the largest corporations today (and subsequently the 2008 crash, which further merged companies in the aftermath).
So, for me the difference is the money being spent here in this 'bubble' isn't like parking new mall shops on various websites, then spending the capital to entice buyers to purchase (either for store products or the store itself) - rather - it seems to me that both private and public sentiment is that the future is bright with the right application of these tools, in the right systems, to promote applicable use cases for things we (humans) can leave up to code/machines.
For instance, one of the most impressive applications of TinyLM uses is setting up several (or dozens) of tiny sensors in say a greenhouse. Each sensor can be linked to a central data repository for active monitoring to deploy active controls - be it barometric pressure, moisture content (soil, air), etc. Linking a bunch of these devices and letting it automatically run, along with linking this sensors as the data-providers to machines that may in turn plant, cull, trim, essentially a fully automated greenhouse.
I'm not greenthumb and I lack in-depth knowledge around how greenhouses (modern or old) work. However, it's without understanding the details I do understand it still takes a (or more) human to maintain the greenhouse.
Consider making these kinds of greenhouses (as is standard in some places now with vertical in-door growing farms) completely autonomous.
That's pretty technologically feasible it would seem with the newest applications of (quote) AI. And it's likely very profitable as well.
If I were to take the same ideology and apply to other industries, I find several applications like the one I mention that would absolutely change how we (humans) live in this (soon to be, IMHO) post-human industrialized world.
So where is all of the doom and gloom from - monopoly, errant comprehension of the technologies, or simply dogma?
It's wild that you can give out gift cards that make your company's value go up so much more than the gift cards could ever cost you. It's almost like one of those financial schemes that end badly.
>Microsoft will also take a minor stake in the 10-month-old Paris-based company, although the financial details have not been disclosed.
Thinking about it, Google or Apple should have got in there with Mistral.
They know someone is going to win big in AI. They lost big on the mobile OS. It is the biggest blunder of Microsoft.
They don’t want to lose on AI. Better to hedge your bets.
They have so much money lying around. Better to invest where they think the puck will be.
Yes AI is hyped but I doubt the bubble will burst. Cheap human like intelligence if achieved via AGI is gonna make them 10x more valuable.
Meta is all in, Google is all in, Microsoft is all in.
Tesla is betting they’ll be the biggest robotics company on the planet.
Getting to AGI is like getting to first nuke for tech behemoths.
I've watched Bill Gates tell Andrew Ross Sorkin during an interview "if it wasn't for the FTC investigating us for the anti-trust lawsuit, we wouldn't have been distracted/took our eye off the prize on mobile"
How sure are we Microsoft "has what it takes/had what it took" to deliver a phone + operating system as polished as Apple?
Windows 11 is very much measurably worse than Mac OS Sonoma. Littered with ads, in between old UI + new UI patterns, etc.
That's 2024
I'm not super confident I'd prefer a Microsoft/Windows mobile OS and therefore I'm not super confident they could actually have delivered a good one
They could have easily been where Android is now if they were two years faster. I think we’d just have a different duopoly and iPhone would still be basically where it is today.
Microsoft-proper hardware is crap, even compared to high-end Google. However, that doesn't matter. My Thinkpad eats Apple hardware for breakfast (as well as anything from Google or Microsoft). Dell has a few nicer laptops in the Precision line which do almost as well as Thinkpad, and definitely better than Apple / Google / Microsoft.
It's the ecosystem.
> Actually I think they’re better at almost everything than Google.
I'd agree, except:
- Hardware
- Office 365 typing synchronization
Google Pixel Pro is quite good (as are most top-of-the-line Google phones), as was the Chromebook Pixel (their top-of-the-line Chromebook, when they made it).
That doesn't mean Windows wasn't absolute dogs--t for many years and isn't riddled with a pile of technical debt. Apple, in contrast, started with NeXTStep. I agree about the specifics you mention (built-in ads and spyware), but the core problems with Windows predate modern Microsoft, and can't really big fixed.
If, in 2024, Microsoft decided to invest in building a real mobile OS, I think they could do okay. The bigger problem would be lack of app ecosystem, and the chicken-and-egg problem with that and users. It's not clear even the best mobile OS could displace Android + iOS.
If I were Microsoft, and I wanted to get in, I'd probably fork Android, to maintain app compatibility. Doing that well would mean killing the goose which is currently laying the golden eggs, though, as it would require replacing Google apps with Microsoft ones. A lot of what makes Android work are free Google accounts, whereas Office 365 is $100 per year. I don't think a Microsoft phone would be competitive unless it had all the same stuff for free, and likely more.
I actually feel like Android is starting to be a little bit vulnerable; a privacy-preserving, non-user-hostile version could have pretty good uptake. Again, not the business Microsoft is in.
Bing has been an also-ran in the search world for a decade (single digit % of search volume compared to Google's 90%+), and AI has shown the first real crack in Google's monopoly.
The future is pretty clearly going to be directly getting AI answers to questions and much less looking at a page of 10 blue links and it's still really unclear if Google is going to make the transition.
with a subscription model, no ads, and therefore no seo manipulation of content/answers. I'm all for it!
[1] https://www.reuters.com/technology/microsofts-bing-plans-ai-...
Except, unlike AGI, nukes happened. We are no closer to AGI than we were when we lived in caves. We found a small local maximum (LLMs), I have seen NO evidence that there is a path from here to AGI.
"Am I close to having gills and breathing underwater?" The fact that I asked, changes nothing.
I am genuinely curious: What do you imagine would be the kind of thing that would be a meaningful step towards AGI?
I have no idea when we'll get there for real, but it seems a pretty big assertion that nothing invented in the last 150 years even helped. So what do you think would help?
I’ll believe we’re closer when we have a computer solve a novel problem that is not a simple pattern match to a similar solution. When a computer can reply to “write me a JIT translator from ARMv5 to ARMv7M” with working code. That takes actual thought and we’re not even close.
3 years to write a JIT from ARMv5 to ARMv7M?
I think your numbers might be off :)
btw, your polit-sci-major no-programming experience sister seems pretty clever if she was able to understand all that. I ran it past a few cavemen I came across and they didn't quite understand the nuances surrounding runtime environment management.
Try it sometime :)
I'll hedge my bets on whether AGI is even possible entirely on how much of an improvement we'll see with GPT5. If it is just a marginal improvement, that's basically it for the current ML bubble.
Edit: i was thinking while walking my dogs, if GPT5 was another great advancement and especially if AGI was around the corner then why would Karpathy leave OpenAI?
Malarkey. Microsoft got where they are in cloud by dogfooding every single piece of software they wrote into their cloud platform, every single service they ran on their gaming platform, and every single user on github and minecraft. After that they turned to corporate customers and forced them into the cloud as well and finally made every single end user of windows sign up too (cant miss any of those precious KPIs.) If they won anything it wasnt through genuine consumer desire to use Azure. The efforts were mostly a shuffling of deck chairs and pump-job similar to the IIS wars on netcraft back in the day where M$ would pump their IIS numbers with static content served from parked websites at hosting providers they paid to switch from Apache.
>They have so much money lying around. Better to invest where they think the puck will be.
they also have a track record of building things no one wants and ruining things everyone likes. Minecraft and Github are demonstrably worse in a lot of ways than they were before redmond took the helm. having a lot of money doesnt make you clairvoyant.
>Meta is all in, Google is all in, Microsoft is all in.
who the fuck cares? these are all companies that exist in the nadier of their innovation. that they collectively scrape barrel to come up with tech memes for the business kids isnt exactly remarkable outside the fact they havent delivered anything of value in so long its surprising we still have to hear about them at all.
>Tesla is betting they’ll be the biggest robotics company on the planet.
The guys who cant get self-drive right? run by the same guy who pedaled twitter into the ground? sure.
AI is a meme for these companies...a parlour trick they use on the money pump for just another year longer before its reinvented into some other nonsensical sci fi pablum for general consumption under the late hour of capitalism.
Edit: typo fix.
In a prior life, our IT manager was the owner of Microsoft productivity products and I was the owner of Azure. We both had drastically different risk profiles and governance needs.
Microsoft already has the cloud infrastructure ready. They don't need to build a new device, or a new operating system, or whatever. They're milking the AI cow as we speak.
Official MS post: https://techcommunity.microsoft.com/t5/ai-machine-learning-b...
Official Mistral post: https://mistral.ai/news/mistral-large/
More discussion: https://news.ycombinator.com/item?id=39511477