Capitalism loves inflection points. The optimists see of AI liberating humanity from employment, while the reality suggests your livelihood will be sacrificed on the altar of mediocrity. Just look at Duolingo and Shopify latest endavors, both championing an "AI-first" company where so-called "agents" replace human workers
llm
In the paper "Hidden Persuaders: Language Models' Political Leanings and Their Influence on Voters", researchers examined the political biases and electoral predictions of various large language models (LLMs). One particularly intriguing finding involved the Mixtral 8X7B model. The base version of Mixtral 8X7B predicted that Donald Trump
NotebookLM gives the same vibes than when animation moved to 3D. The feeling that while it somehow worked it was also lifeless, molding Gen Z's minds into accepting a world where computers produce inferior work to humans, yet profit-driven efficiency still prevails over artistic soul. Don't
LLMs
In recent months, we've witnessed an interesting narrative emerge around Generative AI: Open-source will lead to mass militarization of LLMs. The leap from language prediction to alleged warfare capabilities seems remarkably sudden - and suspiciously convenient. Yet this is precisely the narrative being pushed by VCs, lobbies, and
LLMs
Don’t use agent libraries. Abstractions can be powerful but when dealing with emerging technologies they are definitely overkill and can even burden your projects. That is especially true for generative AI and even more so for agents. I believe there is an ever-growing trend of embedding simplicity within complexity
Think about it for a second. sending back text chunks from documents, based on a query that sometimes isn’t even making sense for a search engine. now add hundred documents, thousands, millions. It will sucks even more. Search is a hard problem to solve and when you add the
The internet is full of code and samples giving you ways to run Flux.1-dev locally but if you are coding an application here is the bare minimum that will get you started. import torch from diffusers import FluxPipeline pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=