A fictitious employee of an Irish aircraft-parts company ended up on a U.S. government restricted-party list. Sixteen years later, companies keep mistaking me for him.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

I'm coming down from spending a few days at Usenix Security, right here in my hometown of Baltimore. This means that my days have been taken up with two kinds of conversation: first, explaining to colleagues why Baltimore isn't actually like The Wire. And second, trying not to talk about AI. Here I'm going to…

Draw any shape and hear it as a drum. Eigendrum solves its real vibration modes with finite elements, so every frequency comes from your outline, not a sample.

Today we're excited to showcase HEIR, the latest powerful tool added to our Private Computing Toolkit. HEIR is an open source compiler that unlocks cryptographically-secure private AI inference.Homomorphic encryptionAs new benefits emerge with the growth of AI, balancing privacy and security is top of mind. Standard protections like end-to-end encryption present a trade-off: user-data can be protected from data breaches, but then the service provider cannot provide features that depend on the data, such as spam or virus detection. Critical sectors like healthcare and finance are even more averse to these risks, and strict regulations limit data sharing across institutions. Alternative mechanisms to provide the same features, like local processing, are limited by the capabilities of the local device and the sensitivity of the service provider's IP. Shipping proprietary AI to a device risks leaking the model.A solution to these issues is homomorphic encryption, a rapidly maturing technology that fundamentally alters this trade-off by allowing computations to be performed directly on encrypted data. Servers can process ciphertexts and return encrypted results without exposing any underlying information. For example, a cloud service can provide content recommendations without being able to see the user's features. This is no exaggeration: one of the demos featured in this post does exactly this. But while homomorphic encryption has a nontrivial cost overhead, it shifts the capability/privacy trade-off to a question of cost. And the cost of homomorphic encryption is rapidly decreasing.Google’s history of innovations in privacy technology—from differential privacy and private set membership to private information retrieval and secure enclaves on Google Cloud—has always focused on securing user data. Homomorphic encryption is another powerful tool we're adding to our private computing toolkit. Like private information retrieval, and in contrast to hardware-based solutions, homomorphic encryption's strong security and privacy guarantees are purely cryptographic. However, manually converting an existing program to use homomorphic encryption efficiently requires a team of cryptographers.About HEIRTo overcome the usability challenges and advance the opportunity homomorphic encryption provides, researchers and engineers at Google built the HEIR compiler project. HEIR (Homomorphic Encryption Intermediate Representation) is an open-source compiler toolchain and development platform for homomorphic encryption. In particular, HEIR can convert pre-trained AI models that operate on unencrypted data to operate on encrypted inputs. Our vision is to make HEIR a one-click solution to enable non-experts to incorporate encrypted inference into production applications.Since announcing our intentions in 2023, we’ve seen the homomorphic encryption community embrace HEIR. We have partnered with companies developing hardware accelerators for homomorphic encryption, including Belfort, Niobium, Cornami, and Optalysys. The fruits of those efforts are shown in our demos below, and we plan to demonstrate the latency benefits of these accelerators in the near future. HEIR has also become a productive research platform. By building on HEIR, cryptographers can focus on their specific optimization and use the existing infrastructure for testing, benchmarking, and comparisons. This has resulted in collaborations with Georgia Tech, Carnegie Mellon, UC Santa Barbara, Illinois Institute of Technology, Purdue, the University of Edinburgh, Tsinghua University, and others. To date, four peer-reviewed publications were built on HEIR, with more in preparation, and HEIR has accumulated numerous citations.Applications of HEIRTo demonstrate how far homomorphic encryption has come, we’re sharing four private inference applications. Each application was compiled with HEIR, and latency numbers are presented for a single-threaded CPU. The source code for all examples is available in our GitHub repository.A Deep Learning Recommendation Model unlocks serving private content recommendations, joint work with Belfort Labs, LG, and New York University.Credit card fraud detection: Together with Niobium and hardshell.ai, we compiled a credit card fraud detector.Threat intrusion: Together with Niobium we compiled the Kitsune system for anomaly detection of encrypted network traffic. This allows a service provider to detect anomalies without revealing the contents of network packets to the service provider.Hotword Detector: Together with Belfort Labs we compiled a hotword detection model, which could allow an audio-triggered AI agent to recognize hotwords while protecting the privacy of the audio recordings.As the software industry adapts to security and privacy changes amid AI, our research team is working to make homomorphic encryption, easy to develop, fast to run, and ubiquitous across industry.

ThoughtDAG is an open-source, local-first canvas where graph edges define the context sent to an LLM. Branch, prune, merge, and inspect what the model sees.

RustDesk brings true unattended remote access to Wayland, with multi-monitor support. A preview build for x86_64 Debian/Ubuntu-based systems is available now.

Security researchers found that in less than 60 seconds, they could open a hatch on a plane’s exterior, plug in a tiny device, and redirect the aircraft’s autopilot or sabotage its flight plan.

Abstract page for arXiv paper 1811.03459: Simplifying and Refactoring Introductory Calculus

Math, Algorithms, Architectures, by hand. Click to read AI by Hand ✍️, by Prof. Tom Yeh, a Substack publication with tens of thousands of subscribers.

We hear it every time we tell people that we push to main and don't use pull requests. Except it is.

Unearthing a 31 year old Easter egg in Ecco the Dolphin

The Magnetophon allowed radio shows to be prerecorded and edited, giving rise to the laugh track and reshaping broadcast programming.

Practical tips for how to run efficient sessions that get the most value from every token.

Command a U.S. submarine across the WWII Pacific. Plot contacts, solve TDC attacks, play the free Silent Shark demo, or get the full game on Steam.

One of the most surprising aspects of the Nix language is that it is lazy, especially if you have never used a lazy language before. This laziness is what makes much of Nixpkgs possible, and its complexity.

Meet Toast 1, Mixedbread's search agent for knowledge-intensive tasks, matching or outperforming Claude Opus 5 and GPT-5.6 Sol while being up to 10× cheaper and 12× faster.

_posted by Stephen De Gabrielle and John Clements_ We are pleased to announce Racket v9.3 is now available from https://download.racket-lang.org/. As of this release:: The `raco setup` command can generate markdown documentation, using the `--doc-mark...

Birds can see ultraviolet light, in addition to the colors that the human eye can see. These groundbreaking photos by Nathan Chronister give us a first glimpse of what birds might look like to other birds.

Place historical images of Richmond, Virginia on the map!

Write a task in plain English. An AI agent runs it on a simulator on your Mac and tells you if a real user could complete it. Save the successful run as a regression check you can replay later.

A blog

Redshift-aware terminal, categorical, and sequential color palettes - carpdiem/ember

A deep-research agent with an enforced budget, verified quotes, and a privacy boundary for local data. - lajosdeme/mole