Con mucho orgullo y felicidad les comparto este nuevo paper que sacamos desde Mercado Libre. Este martes lo voy a estar presentando en SIGIR 2024!
Sabías que las leyes de escalado que dieron origen a los Large Language Models también ocurren en sistemas de recomendaciones?
1/n
Gracias por la invitación! Dejo las slides de la charla "Vibe Coding: Tricks to hold an Agent on a short leash"
https://t.co/gm49JhXlqO
Son lessons learned de intentar hacer un jueguito 99% vibe codeando sin ser dev de juegos.
Podes probarlo aca https://t.co/h0cX31I6YZ
We hosted another LLM-Native meetup at @lemonapp_ar — a space where we bring together founders, engineers, researchers, and AI enthusiasts building frontier products with llms.
Full house again, with 200+ on the waiting list. We dug into real-world technical challenges through 8 talks by 12 experts, sharing insights and practical solutions.
@tadeodonegana (& lemon’s team) @ideasrapidas@IvannaAFigueroa@HeyFardo@manuelsoria_@gptcrosa@shroominic@fpingham
Thanks to all the speakers for making it happen, and to everyone who showed up for the energy and value you brought.
Big thanks to Lemon for opening their doors to host us, and to Tade for helping organize and curate the content.
We’re planning more meetups and growing capacity to keep making space for all the amazing talent pushing this field forward in LATAM.
https://t.co/SXH5HqME8a
@PetralliLucas@fpingham
We hosted another LLM-Native meetup at @lemonapp_ar — a space where we bring together founders, engineers, researchers, and AI enthusiasts building frontier products with llms.
Full house again, with 200+ on the waiting list. We dug into real-world technical challenges through 8 talks by 12 experts, sharing insights and practical solutions.
@tadeodonegana (& lemon’s team) @ideasrapidas@IvannaAFigueroa@HeyFardo@manuelsoria_@gptcrosa@shroominic@fpingham
Thanks to all the speakers for making it happen, and to everyone who showed up for the energy and value you brought.
Big thanks to Lemon for opening their doors to host us, and to Tade for helping organize and curate the content.
We’re planning more meetups and growing capacity to keep making space for all the amazing talent pushing this field forward in LATAM.
https://t.co/SXH5HqME8a
@PetralliLucas@fpingham
En mi caso estoy programando un jueguito qué corre en el browser (nunca hice algo infimamente parecido)
Existe esto? Por ej. Vi un MCP de selenium pero no lo probé aun
Los últimos días vengo metiéndole a aprender a vibe codear. Buenas prácticas y demás.
Me doy cuenta que hay 2 cosas que le darían muchísima más capacidad a cursor:
New 3h31m video on YouTube:
"Deep Dive into LLMs like ChatGPT"
This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their "psychology", and how to get the best use them in practical applications.
We cover all the major stages:
1. pretraining: data, tokenization, Transformer neural network I/O and internals, inference, GPT-2 training example, Llama 3.1 base inference examples
2. supervised finetuning: conversations data, "LLM Psychology": hallucinations, tool use, knowledge/working memory, knowledge of self, models need tokens to think, spelling, jagged intelligence
3. reinforcement learning: practice makes perfect, DeepSeek-R1, AlphaGo, RLHF.
I designed this video for the "general audience" track of my videos, which I believe are accessible to most people, even without technical background. It should give you an intuitive understanding of the full training pipeline of LLMs like ChatGPT, with many examples along the way, and maybe some ways of thinking around current capabilities, where we are, and what's coming.
(Also, I have one "Intro to LLMs" video already from ~year ago, but that is just a re-recording of a random talk, so I wanted to loop around and do a lot more comprehensive version of this topic. They can still be combined, as the talk goes a lot deeper into other topics, e.g. LLM OS and LLM Security)
Hope it's fun & useful!
https://t.co/75mXcUBI8L
Estoy buscando publicar en arxiv el paper que saqué este año (https://t.co/yN4NQLFrxE). Nunca había publicado uno, y para hacerlo necesito un endorsement de alguien que haya publicado al menos 3 papers en Machine Learning.
Algún alma caritativa desea hacerme el endorsement?