🚀 Zaprep: Your Socials on Steroids. Start free — automate 1,000 DMs/month & turn engagement into leads. with 1,000 automated DMs/month.
Submit your Tool
PoweredByAI.app is an AI Tools Directory helping individuals, businesses, and creators discover the best AI tools for writing, coding, design, productivity, and more.
© 2026 , Product of011BQ. All rights reserved.
Anthropic is working on an open source system to verify which AI model produced a given output, according to a blog post published Tuesday. The system,called FlashProve, is built to provide what researchers call “provable inference” — a cryptographic proof, essentially a mathematical guarantee, that a given output came from a specific model. It’s meant to let users confirm that the answer they received really came from the model they think they’re using. Similar tocryptographic email signaturesthat let recipients confirm a message really came from its claimed sender, FlashProve would be robust against impostors attempting to disguise one model as another, even when the impostor is the lab that built and runs the model. In particular, the researchers note that the system could be used to prevent an AI company from secretly swapping in a cheaper model to cut costs, or a more expensive model to inflate its performance results. FlashProve could also be used to verify claims by third parties that a specific task was done by an advanced model. “A developer might claim that their software library was scanned for vulnerabilities by a frontier cybersecurity model, or a company might claim that its business plan was given the go-ahead by an appropriate model,” the researchers write. “How can a user verify these claims?” To work, the system requires AI labs to publish a “fingerprint” of each model they release that can later be matched to specific outputs and verified cryptographically. Crucially, the fingerprints don’t reveal a model’s weights, the internal numbers that define how it behaves and which closed-model makers like Anthropic and OpenAI keep private. That means labs could publish the fingerprints without giving up their most valuable asset, enabling the system to work with commercial models, too. The system is also designed to be lightweight, so verification could be performed on a local device. As part of the announcement, researchers releaseda detailed technical specificationand working code for various elements of the system, which is publicly availableunder an open source license on GitHub. Research in the system is ongoing, and there are no plans to deploy it at Anthropic or any other lab. “This research post is meant to share intermediate progress, and not a completed research agenda,” researchers explain in the announcement post. “We are sharing this explicitly with the goal that others look at what we have done, take it, and improve it.”
View
Enmovil's expansion addresses the need for AI across complex supply chains, where solutions must fit unique customer workflows and operational limits.
View
"Self-hosting GLM brings our blended cost of tokens to 30 cents per million. Our invoice is now one-tenth of what we were spending on Anthropic and OpenAI,” said David Abitbol, who leads AI operation
View
Coforge’s 53.6% Q2 revenue jump includes Encora. The company is moving from selling engineering hours to selling outcomes.
View
The models support multiple Indian languages and target applications ranging from agentic AI and banking to secure, offline deployment across critical sectors.
View
The company will offer affected employees at least six months’ salary and consolidate more product teams in Sydney as part of an organisational restructuring.
View
The model scored 71.8 across three benchmarks, recording a 44 ms response time on an NVIDIA B200 GPU.
View
The company’s adjusted profit rose 20.7% year-on-year, while its proposed ITC Infotech merger remained on track.
View
Their departures come as Claude Code expands its role in Anthropic’s AI coding business.
View
Altman’s recent comment on RAM shortage has reignited the debate over memory allocation between AI data centres and consumer devices.
View
The new capabilities give AI agents business context, enterprise controls and the ability to execute recurring tasks autonomously.
View
OpenAI could be working on a Google Health integration for ChatGPT on Android, which may allow users to connect their health and fitness data to the AI chatbot. The feature could help it analyse information collected through smartwatches and fitness trackers, offering insights based on users' health records. It may also be able to access historical health data and identify patterns over time. The integration has not been officially announced and is not currently available.
View
