Will open source or local llms kill the big AI providers eventually? If so when? I can see maybe basic chat, not sure about coding and images yet
I think the notion of a one size fits all model that is a bit like a sports car in the sense that just get the biggest/fastest/best one is overkill; you use bigger models when needed. But they use a lot of resources and cost you a lot. A lot of AI work isn't solving important math or algorithm problems. Or leet coding exercises. Most AI work is mundane plumbing work, summarizing, a bit of light scripting/programming, tool calling, etc. With skills and guard rails, you actually want agents to follow those rather than get too creative. And you want them to work relatively quickly and not overthink things. Latency is important. You can actually use guard rails to decide when to escalate to bigger models and when not to.
I hope you are not going to say, "to avoid a global recession or depression caused by the popping of the AI bubble". That would be unnecessary and harmful (in its second-order effects), and governments do have advisors who are competent enough in economics to advise against such a move.
If the AI labs become very influential and powerful, Washington might nationalize them, but that would be very different from bailing them out because they have become unprofitable and cannot attract additional investment from the private sector.
GM on the other hand should have been left to die.
However, I was obliquely referring to the open transactionality and patronage encouraged by the current administration, and how the AI / big tech players have, with few exceptions, gleefully joined in.
Unless they run out of money for bribes, I think it's inevitable that current government will bend over backwards to prop them up.
With the recent OpenAi deal with the government I am certain they would throw tons of money at OpenAi if it got real bad. But with upcoming IPO where they are expected to be valued at $840b, we would be a LONG way from them needing a bailout. Well past this current admin.
The reason the banks bailouts did not involve nationalisation is that the US is very reluctant to nationalise anything.
In the UK the first bank to go, Northern Rock, was simply taken over by the government. The shareholders got nothing. The bailout of Lloyds bank required the government taking a 40% stake. This is the way to go - if you need a bailout there should be a cost to the shareholders. otherwise you are just privatising profit and nationalising risk.
Not that UK regulation was great all round or the bailout perfect. It certainly failed to prevent the crisis which could have been done (no doubt the same applies in many countries). I looked at Northern Rock's accounts some time (an year, maybe?) before the crisis and was horrified by their reliance on interbank lending. it was obvious they could not cope with a rise in rates.
Oh easy, with all the drones and sensors, AI means military power. Those who dare opposing the bailout of the local AI gigants want the other side to win.
/s
That's why huge concessions nobody asked for were made to the AI industry in the Big Beautiful Bill.
0: Because the only way to get cache locality out of a LLM is to batch invocations. A centralized system where the server handles thousands of invocations at the same time only needs a tiny fraction of the total memory throughput as having all of those invocations run locally on different machines would.
This will crush OpenAI.
Note: I am not talking about coding here - it will take a while longer but when it is optimized to the bone and llms output has stabilized, you will be running that too on local hardware. Cost will come down for Claude and friends too but why pay 5 when you can have it for free?
In this theory, can you explain why Apple has announced it’s paying Google for Gemini too?
Eventually, this may be true. This autumn? Highly unlikely.
I don't get the financial motive for someone to keep funding these open-weight model training programs other than just purposefully trying to kill the big AI providers.