A new agreement viewed by WIRED gives ICE direct access to a federal database containing sensitive medical data on tens of millions of Americans, with the goal of locating immigrants.

Alors que les nouvelles de fermetures de studios et de redressements judiciaires se multiplient, certaines entreprises parviennent à tirer leur épingle du jeu. C’est le cas de Wētā FX, le studio d’effets visuels aux 7 Oscars et 15 Oscars

The commission, valued at up to £46,000 (including VAT), will see the appointed architect work closely with ateb’s internal teams to deliver a 30-unit housing development, supporting the group’s mission to create better living solutions for the people and communities of West Wales. The two-year contract, running from July 2025 to July 2027, will require the architect to oversee all stages of design, from feasibility through to tender, in line with Welsh Government technical scrutiny and local authority planning requirements. The project is part of ateb’s ongoing commitment to respond to local housing need, regenerate communities, and provide a variety of affordable tenures, including social rent, rent to buy, and shared ownership.Advertisement According to the brief: ‘The ateb Group (where ateb means answer or solution In Welsh) is a unique set o companies that collectively has the shared purpose of 'Creating better living solutions for the people and communities of West Wales. ‘ateb currently has around 3,100 homes predominantly in Pembrokeshire, that we rent on either a social or intermediate rental basis.  ateb works closely with its Local Authority and other partners to develop around 150 new homes every year, to meet affordable housing need through a range of tenures such as, for rent, rent to buy or shared ownership.’ Tavernspite is a small village of around 350 inhabitants located 9.7km southeast of Narberth in Pembrokeshire. Ateb, based in nearby Haverfordwest, is a not-for-profit housing association managing around 3,100 homes across the county. The group’s social purpose is supported by its subsidiaries: Mill Bay Homes, which develops homes for sale to reinvest profits into affordable housing, and West Wales Care and Repair, which supports older and vulnerable residents to remain independent in their homes. Bids will be assessed 60 per cent on quality and 40 per cent on price, with a strong emphasis on experience in the housing association sector and collaborative working with internal client teams.Advertisement Applicants must hold professional indemnity insurance of at least £2 million and be prepared to attend in-person evaluation presentations as part of the assessment process. Competition details Project title Provision of Architect Services for Tavernspite Development Client Contract value Tbc First round deadline Midday, 3 July 2025 Restrictions The contract particularly welcomes submissions from small and medium-sized enterprises (SMEs) and voluntary, community, and social enterprises (VCSEs) More information https://www.find-tender.service.gov.uk/Notice/031815-2025

Outdated coding practices and memory-unsafe languages like C are putting software, including cryptographic libraries, at risk. Fortunately, memory-safe languages like Rust, along with formal verification tools, are now mature enough to be used at scale, helping prevent issues like crashes, data corruption, flawed implementation, and side-channel attacks. To address these vulnerabilities and improve memory safety, we’re rewriting SymCrypt (opens in new tab)—Microsoft’s open-source cryptographic library—in Rust. We’re also incorporating formal verification methods. SymCrypt is used in Windows, Azure Linux, Xbox, and other platforms. Currently, SymCrypt is primarily written in cross-platform C, with limited use of hardware-specific optimizations through intrinsics (compiler-provided low-level functions) and assembly language (direct processor instructions). It provides a wide range of algorithms, including AES-GCM, SHA, ECDSA, and the more recent post-quantum algorithms ML-KEM and ML-DSA.  Formal verification will confirm that implementations behave as intended and don’t deviate from algorithm specifications, critical for preventing attacks. We’ll also analyze compiled code to detect side-channel leaks caused by timing or hardware-level behavior. Proving Rust program properties with Aeneas Program verification is the process of proving that a piece of code will always satisfy a given property, no matter the input. Rust’s type system profoundly improves the prospects for program verification by providing strong ownership guarantees, by construction, using a discipline known as “aliasing xor mutability”. For example, reasoning about C code often requires proving that two non-const pointers are live and non-overlapping, a property that can depend on external client code. In contrast, Rust’s type system guarantees this property for any two mutably borrowed references. As a result, new tools have emerged specifically for verifying Rust code. We chose Aeneas (opens in new tab) because it helps provide a clean separation between code and proofs. Developed by Microsoft Azure Research in partnership with Inria, the French National Institute for Research in Digital Science and Technology, Aeneas connects to proof assistants like Lean (opens in new tab), allowing us to draw on a large body of mathematical proofs—especially valuable given the mathematical nature of cryptographic algorithms—and benefit from Lean’s active user community. Compiling Rust to C supports backward compatibility   We recognize that switching to Rust isn’t feasible for all use cases, so we’ll continue to support, extend, and certify C-based APIs as long as users need them. Users won’t see any changes, as Rust runs underneath the existing C APIs. Some users compile our C code directly and may rely on specific toolchains or compiler features that complicate the adoption of Rust code. To address this, we will use Eurydice (opens in new tab), a Rust-to-C compiler developed by Microsoft Azure Research, to replace handwritten C code with C generated from formally verified Rust. Eurydice (opens in new tab) compiles directly from Rust’s MIR intermediate language, and the resulting C code will be checked into the SymCrypt repository alongside the original Rust source code. As more users adopt Rust, we’ll continue supporting this compilation path for those who build SymCrypt from source code but aren’t ready to use the Rust compiler. In the long term, we hope to transition users to either use precompiled SymCrypt binaries (via C or Rust APIs), or compile from source code in Rust, at which point the Rust-to-C compilation path will no longer be needed. Microsoft research podcast Ideas: AI and democracy with Madeleine Daepp and Robert Osazuwa Ness As the “biggest election year in history” comes to an end, researchers Madeleine Daepp and Robert Osazuwa Ness and Democracy Forward GM Ginny Badanes discuss AI’s impact on democracy, including the tech’s use in Taiwan and India. Listen now Opens in a new tab Timing analysis with Revizor  Even software that has been verified for functional correctness can remain vulnerable to low-level security threats, such as side channels caused by timing leaks or speculative execution. These threats operate at the hardware level and can leak private information, such as memory load addresses, branch targets, or division operands, even when the source code is provably correct.  To address this, we’re extending Revizor (opens in new tab), a tool developed by Microsoft Azure Research, to more effectively analyze SymCrypt binaries. Revizor models microarchitectural leakage and uses fuzzing techniques to systematically uncover instructions that may expose private information through known hardware-level effects.   Earlier cryptographic libraries relied on constant-time programming to avoid operations on secret data. However, recent research has shown that this alone is insufficient with today’s CPUs, where every new optimization may open a new side channel.  By analyzing binary code for specific compilers and platforms, our extended Revizor tool enables deeper scrutiny of vulnerabilities that aren’t visible in the source code. Verified Rust implementations begin with ML-KEM This long-term effort is in alignment with the Microsoft Secure Future Initiative and brings together experts across Microsoft, building on decades of Microsoft Research investment in program verification and security tooling. A preliminary version of ML-KEM in Rust is now available on the preview feature/verifiedcrypto (opens in new tab) branch of the SymCrypt repository. We encourage users to try the Rust build and share feedback (opens in new tab). Looking ahead, we plan to support direct use of the same cryptographic library in Rust without requiring C bindings.  Over the coming months, we plan to rewrite, verify, and ship several algorithms in Rust as part of SymCrypt. As our investment in Rust deepens, we expect to gain new insights into how to best leverage the language for high-assurance cryptographic implementations with low-level optimizations.  As performance is key to scalability and sustainability, we’re holding new implementations to a high bar using our benchmarking tools to match or exceed existing systems. Looking forward  This is a pivotal moment for high-assurance software. Microsoft’s investment in Rust and formal verification presents a rare opportunity to advance one of our key libraries. We’re excited to scale this work and ultimately deliver an industrial-grade, Rust-based, FIPS-certified cryptographic library. Opens in a new tab

Meta is looking to up its weakening AI game with a key talent grab. Following days of speculation, the social media giant has confirmed that Scale AI’s founder and CEO, Alexandr Wang, is joining Meta to work on its AI efforts. Meta will invest $14.3 billion in Scale AI as part of the deal, and will have a 49% stake in the AI startup, which specializes in data labeling and model evaluation services. Other key Scale employees will also move over to Meta, while CSO Jason Droege will step in as Scale’s interim CEO. This move comes as the Mark Zuckerberg-led company goes all-in on building a new research lab focused on “superintelligence,” the next step beyond artificial general intelligence (AGI). The arrangement also reflects a growing trend in big tech, where industry giants are buying companies without really buying them — what’s increasingly being referred to as “acqui-hiring.” It involves recruiting key personnel from a company, licensing its technology, and selling its products, but leaving it as a private entity. “This is fundamentally a massive ‘acqui-hire’ play disguised as a strategic investment,” said Wyatt Mayham, lead AI consultant at Northwest AI Consulting. “While Meta gets Scale’s data infrastructure, the real prize is Wang joining Meta to lead their superintelligence lab. At the $14.3 billion price tag, this might be the most expensive individual talent acquisition in tech history.” Closing gaps with competitors Meta has struggled to keep up with OpenAI, Anthropic, and other key competitors in the AI race, recently even delaying the launch of its new flagship model, Behemoth, purportedly due to internal concerns about its performance. It has also seen the departure of several of its top researchers.  “It’s not really a secret at this point that Meta’s Llama 4 models have had significant performance issues,” Mayham said. “Zuck is essentially betting that Wang’s track record building AI infrastructure can solve Meta’s alignment and model quality problems faster than internal development.” And, he added, Scale’s enterprise-grade human feedback loops are exactly what Meta’s Llama models need to compete with ChatGPT and Claude on reliability and task-following. Data quality, a key focus for Wang, is a big factor in solving those performance problems. He wrote in a note to Scale employees on Thursday, later posted on X (formerly Twitter), that when he founded Scale AI in 2016 amidst some of the early AI breakthroughs, “it was clear even then that data was the lifeblood of AI systems, and that was the inspiration behind starting Scale.” But despite Meta’s huge investment, Scale AI is underscoring its commitment to sovereignty: “Scale remains an independent leader in AI, committed to providing industry-leading AI solutions and safeguarding customer data,” the company wrote in a blog post. “Scale will continue to partner with leading AI labs, multinational enterprises, and governments to deliver expert data and technology solutions through every phase of AI’s evolution.” Allowing big tech to side-step notification But while it’s only just been inked, the high-profile deal is already raising some eyebrows. According to experts, arrangements like these allow tech companies to acquire top talent and key technologies in a side-stepping manner, thus avoiding regulatory notification requirements. The US Federal Trade Commission (FTC) requires mergers and acquisitions totaling more than $126 million be reported in advance. Licensing deals or the mass hiring-away of a company’s employees don’t have this requirement. This allows companies to move more quickly, as they don’t have to undergo the lengthy federal review process. Microsoft’s deal with Inflection AI is probably one of the highest-profile examples of the “acqui-hiring” trend. In March 2024, the tech giant paid the startup $650 million in licensing fees and hired much of its team, including co-founders Mustafa Suleyman (now CEO of Microsoft AI) and Karén Simonyan (chief scientist of Microsoft AI). Similarly, last year Amazon hired more than 50% of Adept AI’s key personnel, including its CEO, to focus on AGI. Google also inked a licensing agreement with Character AI and hired a majority of its founders and researchers. However, regulators have caught on, with the FTC launching inquiries into both the Microsoft-Inflection and Amazon-Adept deals, and the US Justice Department (DOJ) analyzing Google-Character AI. Reflecting ‘desperation’ in the AI industry Meta’s decision to go forward with this arrangement anyway, despite that dicey backdrop, seems to indicate how anxious the company is to keep up in the AI race. “The most interesting piece of this all is the timing,” said Mayham. “It reflects broader industry desperation. Tech giants are increasingly buying parts of promising AI startups to secure key talent without acquiring full companies, following similar patterns with Microsoft-Inflection and Google-Character AI.” However, the regulatory risks are “real but nuanced,” he noted. Meta’s acquisition could face scrutiny from antitrust regulators, particularly as the company is involved in an ongoing FTC lawsuit over its Instagram and WhatsApp acquisitions. While the 49% ownership position appears designed to avoid triggering automatic thresholds, US regulatory bodies like the FTC and DOJ can review minority stake acquisitions under the Clayton Antitrust Act if they seem to threaten competition. Perhaps more importantly, Meta is not considered a leader in AGI development and is trailing OpenAI, Anthropic, and Google, meaning regulators may not consider the deal all that concerning (yet). All told, the arrangement certainly signals Meta’s recognition that the AI race has shifted from a compute and model size competition to a data quality and alignment battle, Mayham noted. “I think the [gist] of this is that Zuck’s biggest bet is that talent and data infrastructure matter more than raw compute power in the AI race,” he said. “The regulatory risk is manageable given Meta’s trailing position, but the acqui-hire premium shows how expensive top AI talent has become.”