In this Q&A, get a glimpse into the future of artificial intelligence (AI) and computer vision through the lens of longtime Unity user Gerard Espona, whose robot digital twin project was featured in the Made with Unity: AI series. Working as simulation lead at Luxonis, whose core technology makes it possible to embed human-level perception into robotics, Espona uses his years of experience in the industry to weigh in on the current state and anticipated progression of computer vision.During recent years, computer vision (CV) and AI have become the fastest-growing fields both in market size and industry adoption rate. Spatial CV and edge AI have been used to improve and automate repetitive tasks as well as complex processes.This new reality is thanks to the democratization of CV/AI. Increasingly affordable hardware access, including depth perception capability as well as improvements in machine learning (ML), has enabled the deployment of real solutions on edge CV/AI systems.Spatial CV using edge AI enables depth-based applications to be deployed without the need of a data center service, and also allows the user to preserve privacy by processing images on the device itself.Along with more accessible hardware, software and machine learning workflows are undergoing important improvements. Although they are still very specialized and full of technical challenges, they have become much more accessible, offering tools that allow users to train their own models.Within the standard ML pipeline/workflow, large-scale edge computing and deployment can still pose issues. One of the biggest general challenges is to reduce the costs and timelines currently required to create and/or improve machine learning models on real-world applications. In other words, the challenge is how to manage all these devices to enable a smooth pipeline for continuous improvement.Also, the implicit limitations in terms of compute processing need extra effort on the final model deployed on the device (that is, apps need to be lightweight, performant, etc.). That said, embedded technology evolves really fast, and each iteration is a big leap in processing capabilities.Spatial CV/AI is a field that still requires a lot of specialization and systems. Workflows are often complicated and tedious due to numerous technical challenges, so a lot of time is devoted to smoothing out the workflow instead of focusing on value-added tasks.Creating datasets (collecting and filtering images and videos), annotating the images, preprocessing/augmentation process, training, deploying and closing the feedback loop for continuous improvement is a complex process. Each step of the workflow is technically difficult and usually involves time and financial cost, and more so for systems working in remote areas with limited connectivity.At Luxonis, we help our customers build and deploy solutions to solve and automate complex tasks at scale, so we’re facing all these issues directly. Our mission, “Robotic vision made simple,” provides not only great and affordable depth-capable hardware, but also a solid and smooth ML pipeline with synthetic datasets and simulation.Another important challenge is the work that needs to be done on the interpretability of models and the creation of datasets from an ethical, privacy and bias point of view.Last but not least, global chip supply issues are making it difficult to get the hardware into everybody’s hands.Data-centric AI is potentially useful when a working model is underperforming. Investing a large amount of time to optimize the model often leads to almost zero real improvement. Instead, with data-centric AI the investment is in analysis, cleaning and improving of the dataset.Usually when a model is underperforming, the issue is within the dataset itself, as there is not enough data for the model to outperform. This could be the result of two possible reasons: 1) the model needs a much larger amount of data, which is difficult to collect in the real world, or 2) the model doesn’t have enough examples of rare cases, which take a lot of time to happen in the real world.In both situations, synthetic datasets could help.Thanks to Unity’s computer vision tools, it is very easy to create photorealistic scenes and randomize elements like materials, light conditions and object placement. The tools come with common labels like 2D bounding boxes, 3D bounding boxes, semantic and instance segmentation, and even human body key points. Additionally, these can be easily extended with custom randomizers, labelers and annotations.Almost any task you want to automate or improve using edge CV/AI very likely involves detecting people for obvious safety and security reasons. It’s critical to guarantee user safety around autonomous systems or robots when they’re working, requiring models to be trained on data about humans.That means we need to capture a large amount of images, including information like poses and physical appearance, that are representative of the entire human population. This task raises some concerns about privacy, ethics and bias when starting to capture real human data to train the model.Fortunately, we can use synthetic datasets to mitigate some of these concerns using human 3D models and poses. A very good example is the work done by the Unity team with PeopleSansPeople.PeopleSansPeople is a human-centric synthetic dataset creator using 3D models and standard animations to randomize human body poses. Also, we can use a Unity project template, to which we add our own 3D models and poses to create our own human synthetic dataset.At Luxonis, we’re using this project as the basis for creating our own human synthetic dataset and training models. In general, we use Unity’s computer vision tools to create large and complex datasets with a high level of customization on labelers, annotations and randomizations. This allows our ML team to iterate faster with our customers, without needing to wait for real-world data collection and manual annotation.Since the introduction of transformer architecture, CV tasks are more accessible. Generative models like DALL-E 2 could also be used to create synthetic datasets, and NeRF as a neural approach to generate novel point of views of known objects and scenes. It’s clear all these innovations are catching the attention of audiences.On the other hand, having access to better annotation tools and model zoos and libraries with pre-trained, ready-to-use models are helping drive wide adoption.One key element contributing to the uptick in computer vision use is the fast evolution of vision processing units (VPUs) that currently allow users to perform model inferences on device (without the need for any host) at 4 TOPS of processing power (current Intel Movidius Myriad X). The new generation of VPUs promises a big leap in capabilities, allowing even more complex CV/AI applications to be deployed on edge.Any application related to agriculture and farming always captures my attention. For example, there is now a cow tracking and monitoring CV/AI application using drones.Our thanks to Gerard for sharing his perspective with us – keep up with his latest thoughts on LinkedIn and Twitter. And, learn more about how Unity can help your team generate synthetic data to improve computer vision model training with Unity Computer Vision.

The IT help desk is evolving. Once defined by queues of tickets and reactive troubleshooting, support today is being reshaped by automation and artificial intelligence (AI). Intelligent systems now assist with everything from b

Trump will continuously monitor all federal workers for "trustworthiness."

Nature, Published online: 02 June 2025; doi:10.1038/d41586-025-01683-yThe poles hold 70% of Earth’s fresh water and are crucial to science; what’s unfolding there as the planet warms deserves greater attention.

Tech layoffs have continued in 2025. Much of that is being blamed on a combination of a slower economy and the adoption of automation via artificial intelligence. Nearly four in 10 Americans, for instance, believe generative AI (genAI) could diminish the number of available jobs as it advances, according to a study released in October by the New York Federal Reserve Bank. And the World Economic Forum’s Jobs Initiative study found that close to half (44%) of worker skills will be disrupted in the next five years — and 40% of tasks will be affected by the use of genAI tools and the large language models (LLMs) that underpin them. In April, the US tech industry lost 214,000 positions as companies shifted toward AI roles and skills-based hiring amid economic uncertainty. Tech sector companies reduced staffing by a net 7,000 positions in April, an analysis of data released by the US Bureau of Labor Statistics (BLS) showed. This year, 137 tech companies have fired 62,114 tech employees, according to Layoffs.fyi. Efforts to reduce headcount at government agencies by the unofficial US Department of Government Efficiency (DOGE) saw an additional 61,296 federal workers fired this year. Kye Mitchell, president of tech workforce staffing firm Experis US, believes the IT employment market is undergoing a fundamental transformation rather than experiencing traditional cyclical layoffs. Although Experis is seeing a 13% month-over-month decline in traditional software developer postings, it doesn’t represent “job destruction, it’s market evolution,” Mitchell said. “What we’re witnessing is the emergence of strategic technology orchestrators who harness AI to drive unprecedented business value,” she said. For example, organizations that once deployed two scrum teams of ten people to develop high-quality software are now achieving superior results with a single team of five AI-empowered developers. “This isn’t about cutting jobs; it’s about elevating roles,” Mitchell said. Specialized roles in particular are surging. Database architect positions are up 2,312%, statistician roles have increased 382%, and jobs for mathematicians have increased 1,272%. “These aren’t replacements; they’re vital for an AI-driven future,” she said. In fact, it’s an IT talent gap, not an employee surplus, that is now challenging organizations — and will continue to do so. With 76% of IT employers already struggling to find skilled tech talent, the market fundamentals favor skilled professionals, according to Mitchell. “The question isn’t whether there will be IT jobs — it’s whether we can develop the right skills fast enough to meet demand,” she said. For federal tech workers, outdated systems and slow procurement make it hard to attract and keep top tech talent. Agencies expect fast team deployment but operate with rigid, outdated processes, according to Justin Vianello, CEO of technology workforce development firm SkillStorm. Long security clearance delays add cost and time, often forcing companies to hire expensive, already-cleared talent. Meanwhile, modern technologists want to use current tools and make an impact — something hard to do with legacy systems and decade-long modernization efforts, he added. Many suggest turning to AI to will solve the tech talent shortage, but there is no evidence that AI will lead to a reduction in demand for tech talent, Vianello said. “On the contrary, companies see that the demand for tech talent has increased as they invest in preparing their workforce to properly use AI tools,” he said. A shortage of qualified talent is a bigger barrier to hiring than AI automation, he said, because organizations struggle to find candidates with the right certifications, skills, and clearances — especially in cloud, cybersecurity, and AI. Tech workers often lack skills in these areas because technology evolves faster than education and training can keep up, Vianello said. And while AI helps automate routine tasks, it can’t replace the strategic roles filled by skilled professionals. Seven out of 10 US organizations are struggling to find skilled workers to fill roles in an ever-evolving digital transformation landscape, and genAI has added to that headache, according to a ManpowerGroup survey released earlier this year. Job postings for AI skills surged 2,000% in 2024, but education and training in this area haven’t kept pace, according to Kelly Stratman, global ecosystem relationships enablement leader at Ernst & Young. “As formal education and training in AI skills still lag, it results in a shortage of AI talent that can effectively manage these technologies and demands,” she said in an earlier interview. “The AI talent shortage is most prominent among highly technical roles like data scientists/analysts, machine learning engineers, and software developers.” Economic uncertainty is creating a cautious hiring environment, but it’s more complex than tariffs alone. Experis data shows employers adopting a “wait and watch” stance as they monitor economic signals, with job openings down 11% year-over-year, according to Mitchell. “However, the bigger story is strategic workforce planning in an era of rapid technological change. Companies are being incredibly precise about where they allocate resources. Not because of economic pressure alone, but because the skills landscape is shifting so rapidly,” Mitchell said. “They’re prioritizing mission-critical roles while restructuring others around AI capabilities.” Top organizations see AI as a strategic shift, not just cost-cutting. Cutting talent now risks weakening core areas like cybersecurity, according to Mitchell. Skillstorm’s Vianello suggests that IT job hunters should begin to upgrade their skills with certifications that matter: AWS, Azure, CISSP, Security+, and AI/ML credentials open doors quickly, he said. “Veterans, in particular, have an edge; they bring leadership, discipline, and security clearances. Apprenticeships and fellowships offer a fast track into full-time roles by giving you experience that actually counts. And don’t overlook the intangibles: soft skills and project leadership are what elevate technologists into impact-makers,” Vianello said. Skills-based hiring has been on the rise for several years, as organizations seek to fill specific needs for big data analytics, programing (such as Rust), and AI prompt engineering. In fact, demand for genAI courses is surging, passing all other tech skills courses spanning fields from data science to cybersecurity, project management, and marketing. “AI isn’t replacing jobs — it’s fundamentally redefining how work gets done. The break point where technology truly displaces a position is when roughly 80% of tasks can be fully automated,” Mitchell said. “We’re nowhere near that threshold for most roles. Instead, we’re seeing AI augment skill sets and make professionals more capable, faster, and able to focus on higher-value work.” Leaders use AI as a strategic enabler — embedding it to enhance, not compete with, human developers, she said. Some industry forecasts predict a 30% productivity boost from AI tools, potentially adding more than $1.5 trillion to global GDP. For example, AI tools are expected to perform the lion’s share of coding. Techniques where humans use AI-augmented coding tools, such as “vibe coding,” are set to revolutionize software development by creating source code, generating tests automatically, and freeing up developer time for innovation instead of debugging code.  With vibe coding, developers use natural language in a conversational way that prompts the AI model to offer contextual ideas and generate code based on the conversation. By 2028, 75% of professional developers will be using vibe coding and other genAI-powered coding tools, up from less than 10% in September 2023, according to Gartner Research. And within three years, 80% of enterprises will have integrated AI-augmented testing tools into their software engineering tool chain — a significant increase from approximately 15% early last year, Gartner said. A report from MIT Technology Review Insights found that 94% of business leaders now use genAI in software development, with 82% applying it in multiple stages — and 26% in four or more. Some industry experts place genAI’s use in creating code much higher. “What we are finding is that we’re three to six months from a world where AI is writing 90% of the code. And then in 12 months, we may be in a world where AI is writing essentially all of the code,” Anthropic CEO Dario Amodei said in a recent report and video interview. “The real [AI] transformation is in role evolution. Developers are becoming strategic technology orchestrators,” Mitchell from Experis said. “Data professionals are becoming business problem solvers. The demand isn’t disappearing; it’s becoming more sophisticated and more valuable. “In today’s economic climate, having the right tech talent with AI-enhanced capabilities isn’t a nice-to-have, it’s your competitive edge,” she said.

Tumor Has ItJun 1, 10:00 AM EDT / by Noor Al-Sibai400 Women Are Suing Pfizer Over Birth Control Shot That Allegedly Gave Them Brain TumorsThe pharmaceutical giant allegedly knew about the risks... but didn't warn patients.Jun 1, 10:00 AM EDT / Noor Al-SibaiImage by Beata Zawrzel / NurPhoto via Getty / FuturismRx/MedicinesRecent research has linked Pfizer's widely-used Depo-Provera birth control shot to massively increased risk of developing brain tumors — and hundreds of women are suing the pharmaceutical giant over it.According to a press release filed on behalf of the roughly 400 plaintiffs in the class action suit, the lawsuit claims that Pfizer and other companies that made generic versions of the injectable contraceptive knew of the link between the shot and the dangerous tumors, but didn't properly warn users.The suit follows a study published by the British Medical Journal last year that found that people who took the progestin-based shot for a year or more were up to 5.6 times more likely to develop meningioma, a slow-building brain tumor that forms, per the Cleveland Clinic, on the meninges, or layers of tissue that covers the brain and spinal cord.Though Pfizer attached warning labels about meningioma to Depo-Provera sold in Canada in 2015 and the UK, Europe, and South Africa after the 2024 study was published, no such label was deployed in the United States — a failure which according to the lawsuit is "inconsistent [with] global safety standards."In an interview with the website DrugWatch, one of the suit's plaintiffs, who was identified by the initials TC, said that she had been "told how great Depo-Provera was" and decided to start it after an unplanned pregnancy that occurred when she'd taken the since-discontinued birth control pill Ortho Tri-Cyclen Lo."I thought it would be more reliable and convenient since I wouldn’t have to take it daily," TC told the site, referencing the four annual injections Depo-Provera requires. "I had no idea it would lead to such serious health problems."After being on the contraceptive shot for three years — and experiencing intense headaches, months-long uterine bleeding, and weight gain — the woman finally consulted her doctor and was diagnosed with meningioma. She's since been undergoing treatment and experienced some relief, but even that experience has been "physically and emotionally draining" because she has to get regular MRIs to monitor the tumor, which likely isn't fatal but still greatly affects her quality of life."It’s a constant worry that the tumor might grow," TC said, "and the appointments feel never-ending."That fear was echoed by others who spoke to the Daily Mail about their meningioma diagnoses after taking Depo-Provera. Unlike TC, Andrea Faulks of Alabama hadn't been on the shots for years when she learned of her brain tumors, which caused her years of anguish.Faulks told the British website that she'd begun taking the medication back in 1993, the year after it was approved by the FDA in the United States. She stopped taking it only a few years later, but spent decades having splitting headaches and experiencing dizziness and tremors. After being dismissed by no fewer than six doctors, the woman finally got an MRI last summer and learned that she had a brain tumor — and is now undergoing radiation to shrink it after all this time."I know this is something I'm going to have to live with for the rest of my life, as long as I live," Faulks told the Daily Mail.Currently, the class action case against Pfizer on behalf of women like Faulks and TC is in its earliest stages as attorneys representing those hundreds of women with brain tumors start working to make them whole.Even if they receive adequate payouts, however, that money won't take away their suffering, or give them back the years of their life lost to tumors they should have been warned about.Share This ArticleImage by Beata Zawrzel / NurPhoto via Getty / FuturismRead This Next

If you’re an ice cream fan, there’s some bad news: One of America’s most beloved ice cream brands may soon see hundreds of its in-store retail locations vanish just as summer is beginning. Thrifty Ice Cream counters, which are found in hundreds of Rite Aid locations in California and other states, are facing an uncertain future thanks to the pharmacy chain’s most recent bankruptcy proceedings. Here’s what you need to know. What is Thrifty Ice Cream? Thrifty Ice Cream is an ice cream brand that is owned by the Rite Aid pharmacy chain. The brand was originally founded in 1940 in Los Angeles, where it was sold from soda fountain counters inside the Thrifty Drug Store chain. The brand is iconic in Los Angeles and throughout California, where its cylindrical ice cream scoops are a summer staple for people who want to cool down with a sweet treat. As the Los Angeles Times reported in 2018, until 1975, a scoop of Thrifty’s ice cream cost as little as five cents, and today scoops cost just a few dollars.   In 1996, the Rite Aid pharmacy chain bought Thrifty PayLess Inc., the then-owner of the Thrifty pharmacy store and Thrifty ice cream, for $2.3 billion. After the acquisition, Rite Aid operated over 500 Thrifty Ice Cream counters inside its pharmacies, mainly in California. But now it is likely these Thrifty Ice Cream counter stores-within-a-store are closing. What will happen to Thrifty Ice Cream? Over the past several days, reports have emerged indicating that up to 500 Thrifty Ice Cream stores may close. When these reports mention “stores” closing, they are referring to the Thrifty Ice Cream counters found in Rite Aid pharmacy locations. Rite Aid is currently undergoing its second bankruptcy in as many years, and the pharmacy chain has already announced plans to close hundreds of locations. It’s important to note that this bankruptcy will mark the end of Rite Aid. All of its stores will either close or be sold to other owners. Locations that that ultimately remain open will no longer be Rite Aid stores. (For example, pharmacy giant CVS has said it will take over 64 physical Rite Aid stores in Washington, Idaho, and Oregon.) In 2018, the Los Angeles Times reported that Rite Aid operated more than 500 Thrifty Ice Cream stations; however, the pharmacy chain has significantly reduced its footprint since then, having gone through its first bankruptcy in 2023. Meanwhile, Thrifty Ice Cream’s online store locator tool appears to be only partially functional as of the time of this writing, so the exact number of locations the brand has is unknown. Fast Company has reached out to Rite Aid for clarity on how many Thrifty Ice Cream counters are still in operation and what their fate will be amid the bankruptcy process. But just because Rite Aid is closing locations and filing for bankruptcy, that doesn’t mean Thrifty Ice Cream is necessarily done for good. After selling off most of its pharmacy assets this month, Rite Aid is expected to hold an auction in June to sell its remaining assets, including the Thrifty brand and the Thrifty Ice Cream factory in El Monte, California. It’s possible that a buyer could swoop in to scoop up the Thrifty Ice Cream brand. If so, any buyer may continue to operate Thrifty Ice Cream stores. The counters in the closing Rite Aid stores would no longer be an option, but a new buyer would be free to open Thrifty Ice Cream individual stores, or form partnerships with other pharmacies or retailers to run Thrifty Ice Cream counters in their stores. Thrifty Ice Cream also currently sells its ice cream at retailers including Vons and Albertsons. A buyer may choose to keep the brand alive through retail outlet sales alone. But for now, all this is just conjecture. We likely won’t know the future of Thrifty Ice Cream until Rite Aid’s bankruptcy is completed, or until next month’s auction.

In this post, we describe FrodoKEM, a key encapsulation protocol that offers a simple design and provides strong security guarantees even in a future with powerful quantum computers. The quantum threat to cryptography For decades, modern cryptography has relied on mathematical problems that are practically impossible for classical computers to solve without a secret key. Cryptosystems like RSA, Diffie-Hellman key-exchange, and elliptic curve-based schemes—which rely on the hardness of the integer factorization and (elliptic curve) discrete logarithm problems—secure communications on the internet, banking transactions, and even national security systems. However, the emergence of Quantum computers leverage the principles of quantum mechanics to perform certain calculations exponentially faster than classical computers. Their ability to solve complex problems, such as simulating molecular interactions, optimizing large-scale systems, and accelerating machine learning, is expected to have profound and beneficial implications for fields ranging from chemistry and material science to artificial intelligence. Spotlight: AI-POWERED EXPERIENCE Microsoft research copilot experience Discover more about research at Microsoft through our AI-powered experience Start now Opens in a new tab At the same time, quantum computing is poised to disrupt cryptography. In particular, Shor’s algorithm, a quantum algorithm developed in 1994, can efficiently factor large numbers and compute discrete logarithms—the very problems that underpin the security of RSA, Diffie-Hellman, and elliptic curve cryptography. This means that once large-scale, fault-tolerant quantum computers become available, public-key protocols based on RSA, ECC, and Diffie-Hellman will become insecure, breaking a sizable portion of the cryptographic backbone of today’s digital world. Recent advances in quantum computing, such as Microsoft’s Majorana 1 (opens in new tab), the first quantum processor powered by topological qubits, represent major steps toward practical quantum computing and underscore the urgency of transitioning to quantum-resistant cryptographic systems. To address this looming security crisis, cryptographers and government agencies have been working on post-quantum cryptography (PQC)—new cryptographic algorithms that can resist attacks from both classical and quantum computers. The NIST Post-Quantum Cryptography Standardization effort In 2017, the U.S. National Institute of Standards and Technology (NIST) launched the Post-Quantum Cryptography Standardization project (opens in new tab) to evaluate and select cryptographic algorithms capable of withstanding quantum attacks. As part of this initiative, NIST sought proposals for two types of cryptographic primitives: key encapsulation mechanisms (KEMs)—which enable two parties to securely derive a shared key to establish an encrypted connection, similar to traditional key exchange schemes—and digital signature schemes. This initiative attracted submissions from cryptographers worldwide, and after multiple evaluation rounds, NIST selected CRYSTALS-Kyber, a KEM based on structured lattices, and standardized it as ML-KEM (opens in new tab). Additionally, NIST selected three digital signature schemes: CRYSTALS-Dilithium, now called ML-DSA; SPHINCS+, now called SLH-DSA; and Falcon, now called FN-DSA. While ML-KEM provides great overall security and efficiency, some governments and cryptographic researchers advocate for the inclusion and standardization of alternative algorithms that minimize reliance on algebraic structure. Reducing algebraic structure might prevent potential vulnerabilities and, hence, can be considered a more conservative design choice. One such algorithm is FrodoKEM. International standardization of post-quantum cryptography Beyond NIST, other international standardization bodies have been actively working on quantum-resistant cryptographic solutions. The International Organization for Standardization (ISO) is leading a global effort to standardize additional PQC algorithms. Notably, European government agencies—including Germany’s BSI (opens in new tab), the Netherlands’ NLNCSA and AIVD (opens in new tab), and France’s ANSSI (opens in new tab)—have shown strong support for FrodoKEM, recognizing it as a conservative alternative to structured lattice-based schemes. As a result, FrodoKEM is undergoing standardization at ISO. Additionally, ISO is standardizing ML-KEM and a conservative code-based KEM called Classic McEliece. These three algorithms are planned for inclusion in ISO/IEC 18033-2:2006 as Amendment 2 (opens in new tab). What is FrodoKEM? FrodoKEM is a key encapsulation mechanism (KEM) based on the Learning with Errors (LWE) problem, a cornerstone of lattice-based cryptography. Unlike structured lattice-based schemes such as ML-KEM, FrodoKEM is built on generic, unstructured lattices, i.e., it is based on the plain LWE problem. Why unstructured lattices? Structured lattice-based schemes introduce additional algebraic properties that could potentially be exploited in future cryptanalytic attacks. By using unstructured lattices, FrodoKEM eliminates these concerns, making it a safer choice in the long run, albeit at the cost of larger key sizes and lower efficiency. It is important to emphasize that no particular cryptanalytic weaknesses are currently known for recommended parameterizations of structured lattice schemes in comparison to plain LWE. However, our current understanding of the security of these schemes could potentially change in the future with cryptanalytic advances. Lattices and the Learning with Errors (LWE) problem Lattice-based cryptography relies on the mathematical structure of lattices, which are regular arrangements of points in multidimensional space. A lattice is defined as the set of all integer linear combinations of a set of basis vectors. The difficulty of certain computational problems on lattices, such as the Shortest Vector Problem (SVP) and the Learning with Errors (LWE) problem, forms the basis of lattice-based schemes. The Learning with Errors (LWE) problem The LWE problem is a fundamental hard problem in lattice-based cryptography. It involves solving a system of linear equations where some small random error has been added to each equation, making it extremely difficult to recover the original secret values. This added error ensures that the problem remains computationally infeasible, even for quantum computers. Figure 1 below illustrates the LWE problem, specifically, the search version of the problem. As can be seen in Figure 1, for the setup of the problem we need a dimension \(n\) that defines the size of matrices, a modulus \(q\) that defines the value range of the matrix coefficients, and a certain error distribution \(\chi\) from which we sample \(\textit{“small”}\) matrices. We sample two matrices from \(\chi\), a small matrix \(\text{s}\) and an error matrix \(\text{e}\) (for simplicity in the explanation, we assume that both have only one column); sample an \(n \times n\) matrix \(\text{A}\) uniformly at random; and compute \(\text{b} = \text{A} \times \text{s} + \text{e}\). In the illustration, each matrix coefficient is represented by a colored square, and the “legend of coefficients” gives an idea of the size of the respective coefficients, e.g., orange squares represent the small coefficients of matrix \(\text{s}\) (small relative to the modulus \(q\)). Finally, given \(\text{A}\) and \(\text{b}\), the search LWE problem consists in finding \(\text{s}\). This problem is believed to be hard for suitably chosen parameters (e.g., for dimension \(n\) sufficiently large) and is used at the core of FrodoKEM. In comparison, the LWE variant used in ML-KEM—called Module-LWE (M-LWE)—has additional symmetries, adding mathematical structure that helps improve efficiency. In a setting similar to that of the search LWE problem above, the matrix \(\text{A}\) can be represented by just a single row of coefficients. FIGURE 1: Visualization of the (search) LWE problem. LWE is conjectured to be quantum-resistant, and FrodoKEM’s security is directly tied to its hardness. In other words, cryptanalysts and quantum researchers have not been able to devise an efficient quantum algorithm capable of solving the LWE problem and, hence, FrodoKEM. In cryptography, absolute security can never be guaranteed; instead, confidence in a problem’s hardness comes from extensive scrutiny and its resilience against attacks over time. How FrodoKEM Works FrodoKEM follows the standard paradigm of a KEM, which consists of three main operations—key generation, encapsulation, and decapsulation—performed interactively between a sender and a recipient with the goal of establishing a shared secret key: Key generation (KeyGen), computed by the recipient Generates a public key and a secret key. The public key is sent to the sender, while the private key remains secret. Encapsulation (Encapsulate), computed by the sender Generates a random session key. Encrypts the session key using the recipient’s public key to produce a ciphertext. Produces a shared key using the session key and the ciphertext. The ciphertext is sent to the recipient. Decapsulation (Decapsulate), computed by the recipient Decrypts the ciphertext using their secret key to recover the original session key. Reproduces the shared key using the decrypted session key and the ciphertext. The shared key generated by the sender and reconstructed by the recipient can then be used to establish secure symmetric-key encryption for further communication between the two parties. Figure 2 below shows a simplified view of the FrodoKEM protocol. As highlighted in red, FrodoKEM uses at its core LWE operations of the form “\(\text{b} = \text{A} \times \text{s} + \text{e}\)”, which are directly applied within the KEM paradigm. FIGURE 2: Simplified overview of FrodoKEM. Performance: Strong security has a cost Not relying on additional algebraic structure certainly comes at a cost for FrodoKEM in the form of increased protocol runtime and bandwidth. The table below compares the performance and key sizes corresponding to the FrodoKEM level 1 parameter set (variant called “FrodoKEM-640-AES”) and the respective parameter set of ML-KEM (variant called “ML-KEM-512”). These parameter sets are intended to match or exceed the brute force security of AES-128. As can be seen, the difference in speed and key sizes between FrodoKEM and ML-KEM is more than an order of magnitude. Nevertheless, the runtime of the FrodoKEM protocol remains reasonable for most applications. For example, on our benchmarking platform clocked at 3.2GHz, the measured runtimes are 0.97 ms, 1.9 ms, and 3.2 ms for security levels 1, 2, and 3, respectively. For security-sensitive applications, a more relevant comparison is with Classic McEliece, a post-quantum code-based scheme also considered for standardization. In this case, FrodoKEM offers several efficiency advantages. Classic McEliece’s public keys are significantly larger—well over an order of magnitude greater than FrodoKEM’s—and its key generation is substantially more computationally expensive. Nonetheless, Classic McEliece provides an advantage in certain static key-exchange scenarios, where its high key generation cost can be amortized across multiple key encapsulation executions. TABLE 1: Comparison of key sizes and performance on an x86-64 processor for NIST level 1 parameter sets. A holistic design made with security in mind FrodoKEM’s design principles support security beyond its reliance on generic, unstructured lattices to minimize the attack surface of potential future cryptanalytic threats. Its parameters have been carefully chosen with additional security margins to withstand advancements in known attacks. Furthermore, FrodoKEM is designed with simplicity in mind—its internal operations are based on straightforward matrix-vector arithmetic using integer coefficients reduced modulo a power of two. These design decisions facilitate simple, compact and secure implementations that are also easier to maintain and to protect against side-channel attacks. Conclusion After years of research and analysis, the next generation of post-quantum cryptographic algorithms has arrived. NIST has chosen strong PQC protocols that we believe will serve Microsoft and its customers well in many applications. For security-sensitive applications, FrodoKEM offers a secure yet practical approach for post-quantum cryptography. While its reliance on unstructured lattices results in larger key sizes and higher computational overhead compared to structured lattice-based alternatives, it provides strong security assurances against potential future attacks. Given the ongoing standardization efforts and its endorsement by multiple governmental agencies, FrodoKEM is well-positioned as a viable alternative for organizations seeking long-term cryptographic resilience in a post-quantum world. Further Reading For those interested in learning more about FrodoKEM, post-quantum cryptography, and lattice-based cryptography, the following resources provide valuable insights: The official FrodoKEM website: https://frodokem.org/ (opens in new tab), which contains, among several other resources, FrodoKEM’s specification document. The official FrodoKEM software library: https://github.com/Microsoft/PQCrypto-LWEKE (opens in new tab), which contains reference and optimized implementations of FrodoKEM written in C and Python. NIST’s Post-Quantum Cryptography Project: https://csrc.nist.gov/projects/post-quantum-cryptography (opens in new tab). Microsoft’s blogpost on its transition plan for PQC: https://techcommunity.microsoft.com/blog/microsoft-security-blog/microsofts-quantum-resistant-cryptography-is-here/4238780 (opens in new tab). A comprehensive survey on lattice-based cryptography: Peikert, C. “A Decade of Lattice Cryptography.” Foundations and Trends in Theoretical Computer Science. (2016) A comprehensive tutorial on modern lattice-based schemes, including ML-KEM and ML-DSA: Lyubashevsky, V. “Basic Lattice Cryptography: The concepts behind Kyber (ML-KEM) and Dilithium (ML-DSA).” https://eprint.iacr.org/2024/1287 (opens in new tab). (2024) Opens in a new tab

For the last 10 years, all of my moves have happened within about a 15-block radius. For personal reasons (a dislike of annoyance and paperwork), I may never leave this neighborhood in Manhattan. Then again, I may not have a choice. You never know when something—a great job opportunity or the sudden desire to experience something new—may come up. If and when you find yourself moving not just locally, but quite a distance, there are some unexpected hurdles you'll need to keep in mind that differentiate this from your standard move. Your budget has to be on pointBudgeting for any kind of move is a key to not going broke during the process, but your expenses for a longer move are going to be more, obviously, and are also going to include quite a few things that you may not immediately think of. Monthly billsIf you're undergoing a more significant move, chances are good that you'll have a rent and utilities overlap, which should be part of your budget planning.In addition to billing overlap, consider any fees you may incur for canceling utility accounts or opening new ones—be sure to check with your new city on how much all of that costs around there. The city you're moving to might have higher taxes, for instance, which may make your monthly bills higher than you expect. You should also think about your other monthly expenses that may change after your move. Your gym membership is a good example. Are you locked into one that is going to be hard to cancel? Many gyms require proof that you're moving out of the region or a certified letter to cancel your membership. On this topic, while it's not quite related to budget, necessarily, check with your doctor, dentist, and other providers about getting referrals, having prescriptions moved to new pharmacies, and if there's anything you should consider related to your healthcare in the new city while you find new providers. Do a quick scan of your checking account to identify any city-specific recurring charges, like public transit passes or bills. Repairs on the new placeRepairs on the old or new home can also add up, especially if you're moving to the new place sight-unseen or if you haven't had a chance to truly assess it. One person I spoke to who moved cross-country, for instance, said the new house they moved to was great—but it had been unoccupied for a while before they moved in, which resulted in spending some time and money cleaning up that they hadn't accounted for.Food and lodgingThe farther you move, the longer you'll spend without a roof over your head and possibly even without a lot of your possessions, as they may still be in transit after you arrive. Don't forget to budget in some money for takeout and even hotel stays, if necessary.Building the budget will take time. Get quotes from a variety of moving companies, figure out your travel situation, add in money for food and bills in the new city, consider whether you need to make any repairs on your old place, and determine what, if anything, it will cost to update your identification and utilities. When you're done ballparking all that, add 10 to 15% onto the number you end up with, advises Rob Rimeris, owner of EverSafe Moving Co. According to him, that "isn't just practical," but "gives people back a sense of agency when plans shift." When you find yourself in a brand-new town, having a sense of agency will keep you feeling sane. How to choose the right moversFinding a good moving company is crucial for any move, but when your stuff is getting hauled across the state—or across the country—it's even more important to do your research. "Find a company that is licensed, insured, has good reviews, and has the proper checks and balances in place," says Charles Chica, co-owner of CT Best Movers. You might be tempted to go with whatever company is the cheapest, but it's important to weight price as just one of many factors.Spend time looking for a company, get your estimates in writing, and provide as much detail as you can about whether you will need help with packing and furniture disassembly and reassembly, as well as what the parking situation is at both the pickup and drop-off locations. Communicate clearly and honestly and make sure all of the communication you receive is backed up in writing. The farther you move, the more complicated this might be, so use an honesty-first approach to avoid any surprise fees or issues.What you might not realize about long-distance movesAlex Girard, whom I interviewed for this story, has lived in four states and recently completed his farthest move. He said that the process for selecting a moving company was trickier than he anticipated, partly because moving works a little differently over long distances."I didn't realize (though it makes sense) that basically the way it works is local movers on either end partner with some national trucking company to do the actual long-haul, so it was kind of hard to compare services," he says. Another difference is that the movers won't load your stuff up and drive directly to your new place, which requires extra planning on your part. "Since the moving companies are partnering with trucking lines," Girard says, "they don't do a special delivery straight to the new house from the old one. Your stuff sits at a warehouse on both sides for a while until they can be loaded onto the next truck out." To avoid the disastrous situation of having to live in a new home with absolutely nothing for two or three weeks, plan for this in advance. Most places Girard spoke to said the boxes and furniture would arrive within 10 to 20 days, so he shipped his most important necessities to his new house in advance, relying on the postal system to make sure he arrived to a new home that contained the essentials he needed to work and live. That was smart, since it actually took a few weeks for the moving companies to deliver everything else, but it was also "a bit expensive."Regardless of how far you're moving, there are things you'll need to keep with you, as movers may not want to (or may not be able to) move all of your belongings. These types of things include identification documents, medications, perishables, hazardous materials, pets (obviously), and even plants. Knowing in advance you'll need to find a safe way to transport all of these and keep them on you is important to ensuring a smooth move. Read online reviews, but don't obsess over themYou'll certainly spend time reading online reviews as you select your moving company—and that's good, but read them with skepticism, too. Girard says he spent a lot of time researching moving companies and pointed out that he read a lot of nightmare-sounding online reviews, but didn't experience anything as catastrophic as what they described. That's a good thing to keep in mind as you do your own research: In general, remember that online reviews only tell part of the story. Someone is more likely to write one when they're super mad and more likely to forget to write one when they have a totally unremarkable experience. Your best bet is to call as many companies as you can, speak to them directly, and make sure they're insured, knowledgeable, and reasonable. (And if you end up having a positive experience with them, consider writing a review just to help out the next person in this position.)Get on the phoneThis is a tip I learned from my mom and am always happy to share: Call people. You can get more done in a 15-minute phone call than a four-day email thread. Whenever she and I go on a trip, she calls the chamber of commerce in that city to ask a local what, exactly, we should be sure not to miss, which has resulted in us having incredible experiences we would never have found if we'd just relied on TripAdvisor or Reddit. The same applies here. Contact your new local government to get a straightforward answer to what, exactly, you need to do to have a smooth move. You'll need a new driver's license, for instance, and the process for obtaining it should be pretty simple, but that can vary by jurisdiction. Turning on your new utilities, updating your mailing address, learning about any new taxes or regulations—all of this should be explained to you by a knowledgeable local. It's likely they'll direct you to an online portal, yes, but you'll know you're working with the right information, which is half the battle. Ask for help from a localFinally, try to find a local who might be willing to answer some questions or tell you more about the town. When I moved from North Dakota to New York at 18, I was enrolled in a university where there were campus reps whose job it was to teach us about the city, but what I learned from them was nothing compared to what I ultimately learned from befriending kids who were born here. City employees can only get you so far. If you don't know anyone in the new place, post an inquiry on Reddit (most cities have their own subreddits—do some Googling to find the most active ones wherever you're moving). In my experience, people love talking up their hometowns. From hidden gems in the culinary landscape to unexpected expenses (Girard notes that he was unpleasantly surprised by the higher taxes on alcohol in his new town), everyday people will be more likely to tell you about the everyday experiences of living there, which will help you acclimate a lot faster.

The idea of using the body’s own organs as mini bioreactors to grow replacement tissue or even regenerate other organs might sound like something out of a science fiction movie, but it's already becoming reality in cutting-edge labs around the world.A collaboration between Wenzhou Medical University, Nanjing University, and the University of Macau has taken an unexpected turn in regenerative medicine by turning to the spleen, a lymphatic organ typically overshadowed by its more high-profile neighbors. Their findings, recently published in Science Translational Medicine, suggest that the spleen could be key to growing new, functional tissues within the body. And the implications are huge, particularly for diseases like type 1 diabetes.Reinventing the Spleen's PurposeRoughly the size of an avocado and tucked under the left side of the rib cage just above the stomach, the spleen’s usual responsibilities include filtering damaged blood cells and supporting the immune system. It’s often considered non-essential as many people live healthy lives without their spleen, if it was removed after injury or illness.But its seemingly simple structure might be exactly what makes it so powerful. With its sponge-like texture, nutrient-rich environment, and proximity to major blood vessels like those of the liver, the spleen turns out to be an ideal candidate for tissue cultivation.Insulin, Made in the SpleenIn this study, researchers set their sights on type 1 diabetes, a condition in which the immune system destroys insulin-producing pancreatic islet cells. Working with the spleens of primates (macaques), the team engineered microenvironments within the test organs to support human pancreatic islets.“We’re essentially converting the spleen into a high-performance bioreactor,” explained study co-author Lei Dong in a press release. “By enhancing extracellular matrix support, accelerating blood vessel growth, and suppressing immune attacks, we’ve created an ideal niche for transplanted cells to thrive.”After transplantation, the human islet cells matured inside the primates’ spleens and began producing insulin and C-peptide (a byproduct of insulin production) continuously for 28 days. It’s a critical proof of concept — showing that not only can the spleen host new tissue, but it can support it long enough to function effectively.This isn't the team’s first foray into reimagining the spleen’s capabilities. They already reprogrammed mouse spleens to perform liver functions, used gene editing to grow liver tissue without transplanting any cells, and even rebuilt thyroid tissue in animal models.Now, the next frontier is personal: using patient-specific induced pluripotent stem cells (iPSCs) to grow customized organs. “The spleen acts like a living bioreactor embedded in our bodies,” said Dong. “With minimally invasive B-ultrasound-guided delivery, we could one day cultivate custom-made organs on demand.”While the concept is promising, clinical use is still a few years away. However, after undergoing thorough safety testing, this work forces a re-evaluation of regenerative medicine and what we consider “non-essential.” The spleen, long overshadowed and often dismissed, might just be one of the body’s most underutilized resources — an internal bioreactor whose potential is only just starting to be realized.This article is not offering medical advice and should be used for informational purposes only.Article SourcesOur writers at Discovermagazine.com use peer-reviewed studies and high-quality sources for our articles, and our editors review for scientific accuracy and editorial standards. Review the sources used below for this article:Science Advances: Transforming the spleen into a liver-like organ in vivoScience Translational Medicine: Islet transplantation in immunomodulatory nanoparticle–remodeled spleensHaving worked as a biomedical research assistant in labs across three countries, Jenny excels at translating complex scientific concepts – ranging from medical breakthroughs and pharmacological discoveries to the latest in nutrition – into engaging, accessible content. Her interests extend to topics such as human evolution, psychology, and quirky animal stories. When she’s not immersed in a popular science book, you’ll find her catching waves or cruising around Vancouver Island on her longboard.