Apple Could Buy Perplexity AI to Finally Catch Up to Rivals
Apple is reportedly considering acquiring Perplexity AI as a strategic move to significantly boost its AI power and catch up ...
Apple is reportedly considering acquiring Perplexity AI as a strategic move to significantly boost its AI power and catch up ...
Using Perplexity AI? Perplexity AI API has two different methods to access. So, here’ the guide to know how to use Perplexity AI in different ways.
As software engineers we are often confronted with the decision of whether to code something ourselves or to add an existing library that does it for us.Whether we like it or not – we are adding dependencies sooner or later. And it's arguably good practice to check a new dependency beforehand: Is it maintained? By whom? How many issues does it have and how many of those are bugs? Are they being fixed? What's on the roadmap? What's the release frequency and how often do APIs break?
I don't normally share side projects here(or in general). Don't have much time to open them up to too much attention. I started this project while riding in a car last weekend. Mainly to explore OpenAI Codex. Using Github mobile I wrote the initial specifications into the readme, and using the ChatGPT iOS app, had Codex build a simple CLI based dungeon master. Switched back to Github for managing the PRs and back and forth for the whole car ride... It kinda got a little out of hand fro
TokenDagger is a drop-in replacement for OpenAI’s Tiktoken (the tokenizer behind Llama 3, Mistral, GPT-3.*, etc.). It’s written in C++ 17 with thin Python bindings, keeps the exact same BPE vocab/special-token rules, and focuses on raw speed.I’m teaching myself LLM internals by re-implementing the stack from first principles. Profiling TikToken’s Python/Rust implementation showed a lot of time was spent doing regex matching. Most of my perf gains come from a) using a faster jit-compile
Artificial Intelligence (AI) is now a part of everyday life. It powers voice assistants, runs chatbots, and helps make ...
From GPT-4 to image generation, PDF summarizing, voice transcription, and more, this all-in-one solution gives you access to powerful AI tools with a one-time payment, and it’s only $29.97 (reg. $234) ...
The explosive growth of LLMs such as GPT-4, Claude, LLaMA, and Grok has intensified concerns around model alignment, toxicity, and data privacy. While many commercial LLM providers have incorporated internal safety mechanisms like Reinforcement Learning from Human Feedback (RLHF) and Moderation APIs, these systems often exhibit limitations: they can over-censor, lack transparency, and are typically rigid or poorly suited to varying regulatory environments.
The tech giant poached several top Google researchers to help build a powerful AI tool that can diagnose patients and potentially cut health care costs.
OpenAI has now created so many new models that even AI experts are finding it hard to keep track, but the company seems to ...
A federal judge in San Francisco ruled late on Monday that Anthropic's use of books without permission to train its ...
As warnings mount about AI’s potential to displace millions of jobs, Anthropic on Friday launched a its Economic Futures ...
In a test case for the artificial intelligence industry, a federal judge has ruled that AI company Anthropic didn’t break the ...
Anthropic, the AI company which Google has invested billions of dollars in, had an extremely wasteful way of gathering the ...
Anthropic didn't violate U.S. copyright law when the AI company used millions of legally purchased books to train its chatbot ...
Claude maker Anthropic's use of copyright-protected books in its AI training process was "exceedingly transformative" and ...
To Anthropic researchers, the experiment showed that AI won’t take your job just yet. Claude “made too many mistakes to run ...
Researchers at Anthropic and AI safety company Andon Labs gave an instance of Claude Sonnet 3.7 an office vending machine to ...
OpenAI announced on Friday it’s launching a research preview of Codex, the company’s most capable AI coding agent yet. Codex is powered by codex-1, a version of the company’s o3 AI reasoning ...
I built a cycling workout generator using a two-stage LLM architecture.Stage 1: Draft generator takes user input and creates high-level workout structure with segments Stage 2: Specialist processors (warm-up expert, interval specialist, etc.) convert each segment into precise power targets and timingsKey insights: - LLMs excel at generating structured JSON when you use schemas - Breaking complex tasks into smaller, focused LLM calls works better than monolithic prompts - Each specialist has isol