Welcome back AI enthusiasts!
In today’s Daily Report:
⚙️OpenAI’s Three New Audio Models to Build Voice Agents
📈New Metric Discovers Moore’s Law for AI Agents
🛠Trending Tools
🥪Brief Bites
💰Funding Frontlines
💼Who’s Hiring?
Read Time: 3 minutes
🗞RECENT NEWS
OPENAI
⚙️OpenAI’s Three New Audio Models to Build Voice Agents
Image Source: OpenAI Developers (i.e., @OpenAIDevs on X)/“Three new state-of-the-art audio models in the API”/Screenshot
OpenAI introduced a new suite of three Audio Models for developers worldwide to build, develop, and deploy Voice Agents.
Key Details:
gpt-4o-transcribe: A speech-to-text AI model powered GPT-4o (“o” for “omni”) to transcribe audio.
gpt-4o-mini-transcribe: A faster, more efficient, and lighter-weight speech-to-text AI model that captures nuances in speech like pauses or fillers.
gpt-4o-mini-tts: A text-to-speech AI model powered by GPT-4o mini (“o” for “omni”) that converts text to natural-sounding spoken audio. It also adapts to requests of speaking styles in prompts like: “Use a pirate voice!”
Why It’s Important:
OpenAI also launched OpenAI.fm, an interactive demo that enables developers to try gpt-4o-mini-tts for free.
AI RESEARCH
📈New Metric Discovers Moore’s Law for AI Agents
Image Source: Model Evaluation & Threat Research (METR)/METR Founder, CEO Beth Barnes/“Measuring AI Ability to Complete Long Tasks”/Screenshot
Model Evaluation & Threat Research (METR) just proposed “50%-task-completion time horizon,” a new metric for measuring AI Performance based on the length of tasks AI Agents can complete.
Key Details:
Despite the rapid progress in AI Benchmarks, their real-world meaning remains unclear. They’re designed to measure domain-specific skills by relying on curated datasets and controlled environments, which don’t reflect the chaos and complexity of real-world tasks.
This new metric compares the length of time it takes a skilled human to complete a real-world task with the length of time it takes an AI Agent to complete the same real-world task with 50% accuracy.
For example, Anthropic’s Claude 3.7 Sonnet has a “50%-task-completion time horizon” of 59 minutes. This statement means it can successfully complete a real-world task with 50% accuracy that takes a skilled human nearly an hour to complete.
Why It’s Important:
This new metric has been “exponentially increasing over the past 6 years, with a doubling time of around 7 months.” This trend suggests that, in under 5 years, AI Agents will be able to autonomously complete real-world tasks that take skilled humans weeks to complete.
AI Experts are referring to this trend as Moore’s Law for AI Performance. In 1965, Gordon E. Moore, the Co-Founder of Intel, made a bold observation that the number of transistors on a microchip doubles roughly every two years.
🩺 PULSE CHECK
Will AI Agents autonomously replace Data Analyst within the next 10 years?
🛠TRENDING TOOLS
🕸️Reworkd effortlessly extracts web data at scale.
💬PromptimizeAI makes you an expert prompt engineer.
🛒20paths makes interactive product demos that convert.
🤝Fellow gives support before, during, and after every meeting.
✂️Wuri turns your ideas into stunning videos with AI-powered editing.
🔮Browse our always Up-To-Date AI Tools Database.
🥪BRIEF BITES
Anthropic announced that you can now use “Claude” to search the internet for up-to-date information relevant to your prompts.
Apple recently shuffled around AI Executive Ranks in an effort to get back on track with integrating Apple Intelligence into Siri.
OpenAI released “o1-pro,” charging developers a whopping $150 per Million Input Tokens and $600 per Million Output Tokens.
Perplexity AI CEO Aravind Srinivas unveiled that he’s upgrading “Deep Research” to think longer, use code execution, and render in-line charts.
💰FUNDING FRONTLINES
BuildOps secures a $127M Series C to build Mission Control for Contractors.
Halliday lands a $20M Series A to build AI Agents that operate safely on Blockchain.
Browser Use raises a $17M Seed Round to make navigating websites easier for AI Agents.
💼WHO’S HIRING?
SoundCloud (New York, NY): Marketing Analytics Intern, Summer 2025
Meta (Los Angeles, CA): Data Scientist, Product Analytics, Entry-Level
Coinbase (San Francisco, CA): Technology Risk Analyst, Mid-Level
Red Hat (Boston, MA): Senior MLOps Engineer, AI Inference, Senior-Level
📒FINAL NOTE
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