Geoffrey Hinton: 200,000 people a year die of incorrect medical diagnoses in the United States. AI will fix that in the next 10 years.

“The easiest way to increase happiness is to control your use of time. Can you find more time to do the things you enjoy doing?” Rest in peace #DanielKahneman

L’application, nommée Nanni AI, utilise l’intelligence artificielle pour interpréter les pleurs de bébé pour proposer aux parents les scénarios les plus probables qui causent ces pleurs. #recherche #médecine #udem #umontreal #ai Mila - Institut québécois d'IA Ubenwa Health bit.ly/3y2Pkug

Nanni AI Knows Why Your Baby Is Crying. Here's How It Does That - CNET cnet.co/4bIQSb9

Nanni AI Knows Why Your Baby Is Crying. Here's How It Does That cnet.com/tech/services-… via CNET

Congrats to Ahmed Rashad and Perle for winning their category at the ACTAI Global Global AI competition! 🏆 Better data with human-in-the-loop is the future, and your platform is a game-changer—empowering knowledge workers and creating jobs globally. Proud to support you!

I'm thrilled that I've recently joined the founding team at Perle as an AI Scientist! We are passionate about empowering teams to bring human wisdom to the heart of their AI. #AI #TechInnovation

Josh Halliday josh halliday reveals the real impact of scope creep in AI annotation projects: 👉Ambiguous business objectives 👉Cross-functional misalignment 👉Endless iteration cycle 👉Undefined technical parameters Perle’s solution — launching soon — uses AI to translate

Legal document analysis is one of the most challenging yet crucial applications for AI. But legal documents written in Arabic present an entirely new challenge for LLM-based AI models due to the language’s rich linguistic features, right-to-left script, and regional dialects.

We’re entering the age of data-aware AI. From cohort-specific labeling to smart dataset distillation, it’s clear: the next frontier isn’t just smarter models—it’s smarter data. That’s what our founding AI scientist Sajjad Abdoli overall takeaway was from this year’s #ICASSP2025.

We can’t predict the future, but our founding AI scientist Sajjad Abdoli believes LLM-assisted coding will evolve to focus on: ✔️Improved security guarantees: Developing formal verification methods for LLM-generated code ✔️Specialized Domain Adaptation: Creating LLMs optimized

LLMs are rapidly transforming software development workflows — anyone can produce functional code from natural language descriptions, suggest optimizations for existing implementations, and identify potential bugs or performance issues. In theory, this sounds great. It reduces

Something interesting is coming...

Peer-Ranked Precision Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery

discuss: huggingface.co/papers/2506.05…

AI is shifting towards a more data-centric approach. But, the widespread adoption of data-centric AI model training is blocked by extraneous circumstances. That means most AI ecosystems continue to rely on data that suffers from crowd-sourced labels, low annotation fidelity,

If your model sees a bee and a flower as one blob in a rectangle, it’s not ready for the real world. The DataSeeds.AI Sample Dataset (DSD), created with our partners DataSeeds.AI, and Brickroad, uses full semantic segmentation, not just bounding boxes to

Meta's $14 billion stake in Scale AI raises a question: Is data labeling the key to unlocking AI's full potential? spectrum.ieee.org/data-labeling-…

Today is a GREAT day for AI! Thank you OpenAI, #gpt_oss_20b

Our founding AI scientist Sajjad Abdoli was quoted in IEEE Spectrum's article on data labeling and the importance of human experts-in-the-loop. He discussed Perle’s recent task: Working with a customer on a model to label images. (1/2)