Activity
Mon
Wed
Fri
Sun
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
What is this?
Less
More

Memberships

Data Alchemy

37.5k members • Free

RYS Status Correction

588 members • $300

307 contributions to Data Alchemy
Another Curriucluum for Learning ML/DS/AI
https://www.geeksforgeeks.org/artificial-intelligence/ai-ml-ds/ > Artificial Intelligence (AI), Machine Learning (ML), and Data Science (DS) are three interrelated fields in computer science and statistics. AI focuses on creating intelligent systems, ML enables computers to learn from data and make predictions, and DS leverages data to extract insights and drive decision-making. These three fields often overlap and complement each other in solving real-world problems and advancing technology.
Stagehand: Open source Browser Automation
It integrates SOTA LLM computer use with coding automation via playwright. """ Why Stagehand? Most existing browser automation tools either require you to write low-level code in a framework like Selenium, Playwright, or Puppeteer, or use high-level agents that can be unpredictable in production. By letting developers choose what to write in code vs. natural language, Stagehand is the natural choice for browser automations in production. 1. Choose when to write code vs. natural language: use AI when you want to navigate unfamiliar pages, and use code (Playwright) when you know exactly what you want to do. 2. Preview and cache actions: Stagehand lets you preview AI actions before running them, and also helps you easily cache repeatable actions to save time and tokens. 3. Computer use models with one line of code: Stagehand lets you integrate SOTA computer use models from OpenAI and Anthropic into the browser with one line of code. 4. """ https://github.com/browserbase/stagehand
DEER-Flow: An OS Deep Research Framework
"DeerFlow is a community-driven Deep Research framework, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community." https://github.com/bytedance/deer-flow
Is AI Conscious
Mo Gawdat has come with a great test. One that he is actually hoping to help people figure out how to run. When you run the double slit experiment in physics. The wave function doesn't actually collapse on the photographic plate, until some living thing observes it. When AI "observation" collapses the wave function, it is sometime of consciousness. BRILLIANT!
1 like • May 6
@Pierre-Henry Isidor You stated, "Because they are conscious does not mean they can observe...," but that is exactly the question. I don't think LLMs could be seen as something that can "observe", and I am not even confident we can get full AGI with just LLMs. Things are changing so fast in this field though, that I may be disproved in 3 years, or less, or a clearly better new architecture may have emerged. But, will they be able to collapse the wave function? And, if so, what does that really mean? We know current machinery does not, and some biological life other than man does. What story do we tell, if we find we can create a machine that simulates consciousness so well, it too can collapse the wave function. No matter what side you are on, if you take the experiment and its outcome seriously, there is an interesting story to create about it.
1 like • May 7
@Pierre-Henry Isidor You seem to keep missing that I do not equate AI with LLMs. I speak strongly against LLMs as either conscious, or even actually intelligent. They are a simulacra of intelligence, but not the actual thing. There is nothing to show that LLMs understand anything. Understanding is not about probabilities, but awareness of learning an actual model, even if the learner does not think of the model as such. LLMs OTOH, simply learn probability distributions. Great for pattern recognition, and zero evidence of actually understanding, although it can pretend to.
MIT Developments in AI Video Generation
- MIT researchers have unveiled CausVid, a generative AI tool that produces high-quality, stable videos in seconds by combining diffusion and autoregressive models. Other MIT projects include new benchmarks for reinforcement learning and improved methods for conveying uncertainty in AI outputs. - https://news.mit.edu/topic/artificial-intelligence2
1 like • May 7
That's a very good amalgamation. I can't imagine it doesn't become the standard, unless some other breakthrough supersedes it.
1-10 of 307
Anaxareian Aia
7
4,015points to level up
@anaxareian-aia-5523
Former software engineer being sucked back into programming because AI. My interest is primarily for my own research and knowledge capture.

Active 11d ago
Joined Apr 23, 2024
Powered by