Cory Doctorow Blasts AI as a Fraud-Filled Bubble
futurism.com
futurism.com
The future will have arrived!
I can run my own mixtral:8x7b-instruct-v0.1-q2 RAG applications on my $1900 Mac Mini, and I now use Ollama for almost all local models.
Cory was not totally negative about AI in this article, but I would have also liked to hear his take on open LLMs.
"But it's not all doom and gloom. Doctorow believes that the situation isn't a zero-sum game, and that once the dust settles, there may be some residual upshots that could drive meaningful technological progress in the future. 'Tech bubbles come in two varieties: The ones that leave something behind, and the ones that leave nothing behind,' Doctorow argued. Following the dotcom bubble popping, millions of young people were lured into the tech sector, creating an 'army of technologists.'"
Transformer neural networks have been catastrophically overhyped - they are considerably dumber than bees - but they are clearly useful for lots of things, and the engineering work on getting them to run cheaply will pay dividends when LLMs are run on more advanced architectures.
LLMs have lots of cool advancements involved in them but isn't what you are being sold. Anybody who knows how these models work and isn't making money off them can explain just how limited they are and how they can't safely be applied at scale. Yet they are doing so anyways. Invest and lie while you can, and get out before it all falls apart.
https://www.searchenginejournal.com/chatgpt-boosts-productiv...
>>A new randomized controlled trial by Harvard and Stanford economists finds that ChatGPT can substantially boost productivity for professionals completing everyday writing tasks.
>>Participants were randomly assigned realistic work simulations with or without access to ChatGPT.
>>Those with access to the AI tool completed assignments 40% faster while producing 18% higher quality output as judged by expert evaluators.
Any assessment of LLMs that overlooks the profound positive impact they are already having on society is completely inaccurate.
Allowing them to do analysis or summary of anything that isn't already in a Wikipedia entry is radically dangerous because of how good they are at hallucinating and lying (and we can't detect that at scale). It is like an automated "yes man". This is the most dangerous bubble in living memory and the cost of it popping will be in the failure of any industry that is foolish enough to rely on them at scale.
And to attack that study in particular, "help people who couldn't write well write better" is complicated, increasing accessibility is good, but there is a BIG difference in an increase in writing quality versus an increase in productivity AND correctness.
Putting aside all of the hype, LLM are already providing enormous productivity boosts in some activities, and those boosts can be fairly characterized as revolutionary when you consider how significant they are and how quickly they came about since GPT2.