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Platform for fast AI-driven physics simulations

Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation

Stephen Wolfram explores the broader picture of what's going on inside ChatGPT and why it produces meaningful text. Discusses models, training neural nets, embeddings, tokens, transformers, language syntax.

Use the power of AI for quick summarization and note taking, NotebookLM is your powerful virtual research assistant rooted in information you can trust.

The largest database of 13,007 AIs available for over 14,372 tasks. Use our smart AI search to find the best AI tools for any use case.

We’re rolling out NotebookLM, an experimental offering from Google Labs to summarize information, complex ideas and brainstorm new connections.

Convert videos into high quality, SEO optimized blog articles with AI. The #1 video to text converter. Great for summarizing YouTube videos. Free for 3 blogs/month.

Bard is now Gemini. Get help with writing, planning, learning, and more from Google AI.

Talk with Claude, an AI assistant from Anthropic

Microsoft Copilot leverages the power of AI to boost productivity, unlock creativity, and helps you understand information better with a simple chat experience.

Talk with Claude, an AI assistant from Anthropic

Get up to speed on the hottest topic in UX with this collection of resources, including expert opinions, tool recommendations, and practical applications of AI in research and design.

Transcribe audio and video in 100+ languages with just a few clicks! Riverside's transcriber offers accurate AI transcriptions completely free!

These on-demand courses, labs and videos about generative AI will help you reach your professional goals and boost your value as an employee.

Bard is now Gemini. Get help with writing, planning, learning, and more from Google AI.

Make original music and sound effects using artificial intelligence, whether you’re a beginner or a pro.

KREA – Generative AI made easy. Generate and enhance images and videos using powerful AI for free.

Build intelligent ideas with our platform for local AI

Dropbox added some new AI features. In the past couple of days these have attracted a firestorm of criticism. Benj Edwards rounds it up in Dropbox spooks users with new …

Learn full-stack web development with Kent C. Dodds and the Epic Web instructors. Learn TypeScript, React, Node.js, and more through hands-on workshops.

Qwiklabs provides real Google Cloud environments that help developers and IT professionals learn cloud platforms and software, such as Firebase, Kubernetes and more.

0:00 - Introduction1:47 - PortSwigger Academy4:12 - Exploiting LLM APIs with Excessive Agency10:21 - Exploiting Vulnerabilities in LLM APIs18:19 - OutroThank...

Sora is an AI model that can create realistic and imaginative scenes from text instructions.

QR Code AI Art Generator Blend QR codes with AI Art

A few days back, a user on Reddit shared these images:

Language models (LMs), such as GPT-4, are at the forefront of natural language processing, offering capabilities that range from crafting complex prose to solving intricate computational problems. Despite their advanced functionalities, these models need fixing, sometimes yielding inaccurate or conflicting outputs. The challenge lies in enhancing their precision and versatility, particularly in complex, multi-faceted tasks. A key issue with current language models is their occasional inaccuracy and limitation in handling diverse and complex tasks. While these models excel in many areas, their efficacy could improve when confronted with tasks that demand nuanced understanding or specialized knowledge beyond their general capabilities.

In the evolving landscape of natural language processing (NLP), the ability to grasp and process extensive textual contexts is paramount. Recent advancements, as highlighted by Lewis et al. (2021), Izacard et al. (2022), and Ram et al. (2023), have significantly propelled the capabilities of language models, particularly through the development of text embeddings. These embeddings serve as the backbone for a plethora of applications, including retrieval-augmented generation for large language models (LLMs) and semantic search. They transform sentences or documents into low-dimensional vectors, capturing the essence of semantic information, which in turn facilitates tasks like clustering, classification, and information retrieval.

Get up and running with large language models.