Leaked Google Letter, Open Source the Threat or Opportunity?

It's difficult to keep up with AI news. And recent news suggests that it's also difficult for the software giants to keep up with Open Source AI models. On May 4th Semi Analysis leaked an internal letter from within Google, seemingly from a software engineer that reveals a number of significant issues that the Open Source community present to both Google and Open AI.

Below are some of the revelations in the letter:

'the uncomfortable truth is, we aren’t positioned to win this arms race and neither is OpenAI. While we’ve been squabbling, a third faction has been quietly eating our lunch.

I’m talking, of course, about open source. Plainly put, they are lapping us. Things we consider “major open problems” are solved and in people’s hands today.'

'Open-source models are faster, more customizable, more private, and pound-for-pound more capable. They are doing things with $100 and 13B params that we struggle with at $10M and 540B. And they are doing so in weeks, not months. This has profound implications for us:

We have no secret sauce. Our best hope is to learn from and collaborate with what others are doing outside Google. We should prioritize enabling 3P integrations.
People will not pay for a restricted model when free, unrestricted alternatives are comparable in quality. We should consider where our value add really is.
Giant models are slowing us down. In the long run, the best models are the ones which can be iterated upon quickly. We should make small variants more than an afterthought, now that we know what is possible in the <20B parameter regime.

The whole letter is fascinating and poses many questions. Legislation for AI usage, by government is useless if it just imagines that it is the tech giants that can be legislated against. Legislation about safeguards or bias or some such has been made redundant. Innovation is out of the hands of the giants. And they know it.

What the Semi Analysis article demonstrates so well is the pace of Open Source development. What costs the giants millions and many months to do, is done in days and for little outlay by the collective. Some of which I've managed to catch and commented on in this blog. This all reemphasises, to me, that Bard's response to the UK Governments white paper on AI being: too slow, too bureaucratic, too focused on compliance, may be true of Big Tech too.

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