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Malý produkt velké spolupráce Intelu s Nvidií na trhu uvidíme v roce 2028. Nvidia, snad i po zkušenostech s GB10 / N1X, chce po ARM vyzkoušet i x86 řešení. Intel si zase ukousne z léta odříkaného chleba…

Nové retro véčko od značky Commodore nabízí lidem digitální detox • Evropský operační systém Sailfish zablokuje sociální sítě i prohlížeče • Omezený telefon s klávesnicí T9 bude v prodeji koncem roku 2026

Because generative AI (genAI) tools and services have become so ubiquitous (and popular), the costs of using them are going through the roof — leading to an insatiable appetite for tokens.

Tokens represent a common way to measure and price AI use. Much like letters and words in English, large language models (LLMs) grasp a sentence or query by breaking words into tokens.

With the AI explosion well under way, tokens are now “the fundamental units of data our models process, many representing a problem being solved,” according to Google CEO Sundar Pichai. (Google, by the way, processes about 3.2 quadrillion tokens a month.)

But as the price of all those tokens adds up, business and IT execs are looking for ways to cut costs while keeping corporate productivity up. Uncontrolled token use has already landed one company with an unexpected $500 million AI bill. 

There are a number of ways companies can rein in the price of AI at the model, infrastructure, silicon, and business levels. Here’s a look at how some of those savings might actually be achieved.

Switch to lower-cost models

One way of potentially saving money is by re-routing AI work to a cheaper model, Pichai said. At Google that would Gemini 3.5 Flash. It delivers “frontier-level capabilities at less than half the price of comparable frontier models.

“If companies use a mix of [Gemini 3.5] Flash and other frontier models, they could save a lot of money,” Pichai said.

Those kinds of models provide cheaper tokens, with reasoning that’s good enough for many users — if not as strong as mainstream Gemini 3.5 — to deliver useful results.

“There is sometimes overkill with the [LLMs],” said Deepak Seth, senior director analyst at Gartner. “I don’t always need a large language model which has been trained on the works of Charles Dickens and Shakespeare and Harry Potter.”

Hyperframe Research principal analyst Steven Dickens can’t stop using Amazon’s Quick, which costs $20 a month, for personal tasks. “It is great personal ROI as it has not only made tasks faster, but unlocked tasks I would never have even attempted previously,” Dickens said.

Don’t forget the hardware and software part of the equation

The token crisis isn’t new, said Dheeraj Pandey, CEO of DevRev, who likens what’s going on now in the AI market to the disruptions that emerged with the arrival of cloud computing and virtualization years ago. 

“We let chaos reign and then we had to rein in the chaos,” Pandey said. “The word that people started using was server consolidation and virtualization.”

The answer to the token problem, he said, is the same: “Anything in systems can be solved with caching and indirection.”

DevRev, for example, is building a memory layer between AI agents and primary data sources, such as Salesforce or ERP records; that can cut token load and make data movement more efficient. The layer holds a knowledge graph with answers to common agent questions and runs on cheaper CPUs, avoiding more costly GPU cycles.

Sending agents straight at systems like ServiceNow and Salesforce “will burn a lot more tokens. It’s also not precise. And finally, it’s not safe enough where I can roll it back in case an agent has committed a mistake,” Pandey said.

Network automation firm NetBrains uses a different method: It uses conventional computing to map a network’s layout then feeds only key information to models for planning and reasoning, where AI excels. “So you don’t have to spend all the tokens,” said Netbrains CTO Sang Peng.

Focus on prompt efficiency

Staffing firm ManpowerGroup has found that prompt efficiency can be an effective tool for improving token use, both internally and externally for clients.

For example, users accessing its internal labor-market tool initially needed 10 follow-up questions to drill into a query. A year later, more efficient use of prompts has brought that number down to an average of four, said Max Leaming, head of data science and AI solutions at ManpowerGroup. 

“They’re using fewer tokens and they’re simply more efficient,” he said. “And that in large part has to do with your ability to prompt efficiently.”

Go local

New AI hardware that generates free tokens at home could ease some of the cost crisis.

At GTC Taipei earlier this month, Nvidia and Microsoft unveiled RTX Spark, an agentic AI desktop PC that runs agents and 120-billion-parameter models locally on Windows. The goal is “to deliver unmetered intelligence to every home and every desk with Windows,” Microsoft CEO Satya Nadella said in a statement.

Some companies are looking to reduce cloud AI costs by putting their own hardware in data centers, with vendors such as HPE and Dell providing servers installed in independent facilities. (On-premise AI is gaining ground amid sovereign AI and geopolitical concerns, including the recent conflict in the Middle East, where large data centers were struck with missiles.)

“There are local, region-specific and multiple vendor AI solutions. All of those things can help mitigate the risk. But they’re not going to eliminate it,” said Max Goss, senior director analyst at Gartner.

Use forward-deployed engineers

Reducing token costs is something that may fall to forward-deployed engineers (FDEs) in customer environments, said Taimur Rashid, managing director of AWS’s Generative AI Innovation Center.

“I expect these teams to be able to architect systems that have those cost requirements in mind, whether it’s use a different model or a different use case that doesn’t increase the per-token cost,” Rashid said.

Companies may spend heavily on token consumption, “but if you’re generating revenue, as long as the economics work out, then you’re at peace,” Rashid said.

The use of FDEs is gaining ground as IT decision-makers look to both rollout successful AI deployments while also keeping an eye on costs.

Change the measure of success from tokens to outcomes

Even with the current emphasis on reducing token use to save money, the metrics used to measure AI success are likely to shift, Gartner’s Seth said. At some point, token-based pricing will move more toward an outcome-based model, where the unit of value is outcomes, not fragments of words.

“Some companies are moving towards outcome-based pricing,” Seth said. “When people start realizing the real cost of tokens, then companies will start looking at token efficiency.”

EU sází na čipy, cloudy a AI, byznys ale postrádá deregulaci a jednotný trh • . • Technologickou suverenitu mají zajistit nové úřady, audity a další pravidla. • Firmy varují, že přeregulace brzdí inovace, investice i rozvoj AI v Evropě.

V červnu má odstartovat raketa Pegasus XL, která do vesmíru vynese družici LINK • Během několika týdnů se přiblíží k observatoři Swift a vytáhne ji na vyšší dráhu • Pokud se mise nezdaří, družice shoří v atmosféře

Výtěžnost procesu Intel 18A, o jehož využití Apple uvažuje, stále není taková, aby Apple motivovala k podpisu smlouvy. Výrobce ARM procesorů proto ještě počká, nikoli však neomezeně dlouho…

Byla vydána nová verze 15.1 svobodného unixového operačního systému FreeBSD. Podrobný přehled novinek v poznámkách k vydání.

Cybercrime now accounts for more than 30 percent of all offenses across the Asia and South Pacific (ASP) region, according to the latest figures from Interpol. The international cop shop said on Wednesday that the region has seen “a dramatic increase” in the number of recorded cybercrimes, driven largely by an uptake of digital infrastructure, new technologies, and the increasingly organized nature of criminal networks. Interpol’s latest ASP Cyberthreat Assessment Report states that online scams and phishing attacks dominate cybercrime in the region. Data taken from 2024-2025 shows that phishing campaigns have matured beyond the spray-and-pray mass emails of yesteryear and now resemble the more sophisticated techniques deployed elsewhere in the world. Targeted spear phishing is more common nowadays, and the growing use of AI helps even low-skilled script kiddies to apply a layer of authenticity to their attacks. The region’s problem with organized scamming gangs that run camps where hundreds of people are compelled to commit crimes is especially pronounced and well-documented. A United Nations report published last year described scam call centers across Southeast Asia as an epidemic that is metastasizing across the region “like a cancer.” These compounds can be found across countries such as Cambodia, Laos, Myanmar, and the Philippines, and often see vulnerable individuals trafficked into the scam centers to work under poor conditions – or even as slaves. Interpol cited Singaporean research, which estimated the regional scam industry generates close to $40 billion each year. AI tools, especially those capable of generating convincing deepfake imagery, have also proven popular with cybercriminals across ASP, just as they have beyond the region. In 2024, the same scam compounds were found using deepfake imagery to support romance scams. In February 2024, an employee at a multinational business in Hong Kong was duped into authorizing a $25 million payment because the faces of company execs were convincingly deepfaked on a video call. A similar case was also reported in Singapore in March 2025, when a finance director at a different multinational was tricked into transferring more than $499 million following a Zoom call in which fraudsters assumed the identities of company chiefs, including the CEO and CFO. Interpol’s report highlights how cyber threats are evolving into large-scale challenges for multiple jurisdictions, and no longer represent relatively uncommon, isolated incidents. While digitization across the region is growing, opening new economic opportunities for these countries, law enforcement agencies are struggling to keep pace with the increase in cybercrime. Many lack the skills and tools needed to investigate these crimes. The issue is especially pronounced in developing countries and small island states in the Pacific, which face “significant resource and capacity constraints,” and are thus more vulnerable to direct targeting in attacks by criminals who have a greater chance of evading consequences. Neal Jetton, cybercrime director at Interpol, said: “The findings in this report highlight a rapidly evolving cyber threat landscape across Asia and the South Pacific, where cybercriminals are leveraging artificial intelligence, ransomware-as-a-service models, and sophisticated social engineering techniques on an industrial scale. “As digital adoption accelerates across the region, strengthening operational cooperation, information sharing, and cyber resilience remains essential to protecting communities and critical infrastructure.” Some improvement Interpol lauded many jurisdictions and governments within the ASP region for their proactive approaches to countering cybercrime growth. Hong Kong and the Republic of Korea are two areas that have made strides by introducing new cybersecurity legislation, while others have established national task forces, codified national action plans, and launched awareness campaigns. But even in more developed countries globally, and those with more mature cybersecurity regulatory and legislative landscapes, the issue of increasing rates of cybercrime persists. While Interpol does not collect cybercrime figures for other regions, such as Europe and North America, in the same way that it does for ASP, it’s easy to see that problems persist everywhere. The UK’s Office for National Statistics (ONS) publishes crime rates by type across England and Wales each year, and while computer misuse offenses in 2025 decreased by 58 percent compared to 2017’s figures, there were still an estimated 735,000 cases across the year. Expanding the data to look beyond pure cyber offenses to cyber-supported crimes, such as banking and credit fraud, these offenses account for more than 2.7 million of the circa 9.6 million total crimes committed. The FBI in the US produces its annual IC3 report examining the rates of cybercrime across the country. Although it doesn’t compare it to total offenses or other crime types, the latest report reflecting 2025’s figures showed cybercrime reports topped one million for the first time, and total losses reached a record $20.87 billion. ®

OpenAI appears to be testing a new subscription and experience for science use cases, but it's unclear if it'll be available to everyone regardless of their background. [...]

A federal judge has rebuffed Workday’s claim that it cannot be held liable under California anti-discrimination laws when its tools are used to screen (and potentially reject) job candidates in other states.

This week, US District Judge Rita Lin indicated that she will likely allow additional state discrimination claims against Workday to move forward. This would significantly expand the closely-watched case and likely ratchet up scrutiny of AI recruiting tools and their potentially inherent biases when it comes to age, race, sex, disabilities, and other factors.

Further, it could indicate that, even if a company is not the final employer, it may be held liable if its tools materially influence who gets rejected. This could set new legal standards for AI hiring systems, and have implications across industries, experts note.

“This case reinforces the importance of actually managing AI risks,” said Valence Howden, advisory fellow at Info-Tech Research Group. “If an AI-enabled model or ATS [Applicant Tracking System] is making decisions based on historical information, it can raise questions about whether bias in outcomes and datasets has been properly addressed.”

The case so far

Mobley v. Workday, Inc. alleges that Workday’s AI screening tools discriminate against job seekers based on age, race, and disability. The suit was filed in 2024 in the US District Court of California by Derek Mobley, a Black disabled man over 40, who claimed Workday’s algorithms continually screened him out as he applied for more than 100 positions on the platform.

The claims alleged discrimination prohibited by several US and California statutes: Race and sex under the Civil Rights Act of 1964 (Title VII); disability under the Americans with Disabilities Act of 1990 (ADA); age under the Age Discrimination in Employment Act of 1967 (ADEA); and race, gender, and age under California Fair Employment and Housing Act (FEHA).

Specifically, the suit centered around Workday’s use of automated, algorithm-driven tools for applicant screening. It alleged that these systems rely on historical data and statistical modeling that can make them susceptible to existing biases, even if protected characteristics like race, age, sex, or disability are not explicitly provided.

Bias may enter these systems in different ways, the plaintiffs argued, including via training data, model design, and evaluation criteria for candidate fit. The system could reproduce discriminatory outcomes by making correlations from data. For instance, years of experience on a resumé may indicate age; long employment gaps may infer a disability or caregiving responsibilities; educational and institutional affiliations could reflect race.

Workday has argued that it is not subject to liability under employment statutes because it does not qualify as the job applicants’ “employer.” But federal judges have allowed key parts of the lawsuit to move forward, ruling that Workday could potentially be treated as an employer’s “agent” for the purposes of anti-discrimination law.

The latest dispute centers on FEHA. According to legal sources, the California statute is among the strongest anti-discrimination laws in the US, in many cases providing broader protections than federal employment laws.

Workday asked the court to dismiss claims brought under California law, saying FEHA should not apply to the hiring decisions of out-of-state employers and applicants. The company’s lawyers argued that enforcing this would effectively allow California law to supersede that of other states, just because a company used their platform.

But Lin disagreed, saying FEHA does apply, and in fact, Workday is directly liable for its “own engagement in FEHA-regulated activities on the employer’s behalf.” Holding businesses liable for “their own discriminatory conduct” is within the scope and purposes of FEHA and consistent with public policy.

However, the issue is still to be decided; Lin did not indicate when she would release a final ruling.

Workday’s defense

A Workday spokesperson called the claims in the suit “false.”

“Workday’s AI recruiting tools don’t make hiring decisions and are designed with human oversight at their core,” the spokesperson told CIO. “Our technology looks only at job qualifications, not protected traits like race, age, or disability. We rigorously test our products as part of our responsible AI program to confirm our tools do not harm protected groups.”

Workday’s platform is meant to provide insights on how well a candidate’s qualifications match the requirements of a posted job, the company said. Those tools focus only on qualifications listed in a candidate’s application, which are compared to qualifications identified by the employer as important for the job.

Workday’s Chief Responsible AI Officer Kelly Trindel said its AI does not make employment decisions, automatically reject candidates, or determine who gets a job; further, she said, there is no evidence that the company’s tools result in harm to protected groups.

Trindel, who is former chief analyst of the Equal Employment Opportunity Commission (EEOC), leads a dedicated team composed of psychologists and PhD-level data scientists whose sole focus is to ensure that its AI is “responsible, fair, and ethical.” She said that the company’s AI systems undergo ongoing reviews throughout their lifecycle to help prevent unintended consequences, and Workday is “committed to accountability, transparency, and trust,” and invests “significant resources” into identifying and mitigating bias.

Further, she said, Workday has a company-wide commitment to ethical AI, and an independently-evaluated AI governance program based on standards from the National Institute of Standards and Technology (NIST) and the International Standards Organization (ISO).

“Workday builds AI to support people, not replace them, and this is of particular importance when it comes to hiring,” Trindel noted. Its platform is designed to help employers “manage high-volume processes more efficiently, surface relevant information, and reduce administrative work so teams can spend more time applying their expertise and judgement to hiring decisions.”

What this means for enterprise leaders

Workday isn’t alone in its legal challenges; other AI hiring tools are also being scrutinized over their methodologies, algorithms, and data-collecting practices. Eightfold, for one, is also facing a California class action lawsuit alleging that its tools unfairly rely on job candidates’ online data to predict whether they’d be a good fit for a position.

This means that enterprises, who are already feeling increased pressure to document hiring decisions, conduct AI bias audits, and maintain human oversight in recruitment and hiring, must be even more diligent in their vetting of AI tools.

Organizations must be actively defining how these recruitment tools should work, identifying bias in their algorithms, and setting up structures to test for bias across the tools’ decision-making logic, Info-Tech’s Howden advised.

“Validation of non-biased outcomes also needs to be active and ongoing, rather than a point-in-time exercise,” he said.

While Workday and others say human oversight is paramount, “it’s hard to incorporate humans into the process if the platform does the weeding out before humans have the ability to intervene,” Howden pointed out.

Discriminatory biases can exist in past hiring decisions, so it’s easy to forget that AI can “emulate and adapt those biases as part of its perspective,” he said. That includes how AI looks at language: Different cultures use different phrasing, and AI can capture that and use it to exclude candidates.

Ultimately, he called the case a “cautionary tale” illustrating how lightly some organizations have been treating AI risk. It also highlights the urgency involved in building out more advanced enterprise risk practices, “rather than relying on the limited capabilities they may have employed up until now.”

This article originally appeared on CIO.com.

For generations, technology export controls referred to the transfer of source code to other countries. But that no longer works, as the latest Anthropic fight with the US Commerce Department makes clear. 

On Friday, Anthropic announced that it had received instructions from Commerce “to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Anthropic models will not be affected.” 

Technically, the Commerce letter doesn’t explicitly say that, but lawyers and consultants argue that, when combined with an earlier executive order declaring Anthropic a supply chain risk, that very well might be what it means.

What the Commerce letter says is that Anthropic needs a license to export Fable 5 and Mythos 5 (a “deemed export“), listing four circumstances in which that license would be required: “The sending or taking of the model out of the United States in any manner; The sending or taking of the model from one foreign country to another in any manner; Retransferring the model within a single foreign country; or the release of the model to a ‘foreign person’ in the United States or a foreign country.”

Restricts capabilities not code

Although moving a model has historically meant transferring the source code, most experts argue that the definition has changed for all SaaS deployments, and could now be interpreted as referring to any access to the models.

“This is not just about data sovereignty anymore. It is about capability sovereignty, where governments want to control who has access to frontier AI capabilities, irrespective of who built it, where it is hosted, or who worked on it,” said Valence Howden, advisory fellow at Info-Tech Research Group.

“The reference to deemed exports is important, because traditionally that would apply to source code, technology, or technical knowledge being transferred,” he said. “In this case, the thing crossing borders is not necessarily the model itself, but it is access to the capability. That is a significant shift, and signals the real intent behind the AI arms race. The focus is moving from controlling the technology to controlling access to the outcomes the technology can produce.”

Mark Rasch, a former federal prosecutor who specializes in legal technology issues, agreed. “I don’t need to have the source code physically resident in order to take advantage of the capabilities of that code. Today, the location of the source code is irrelevant.”

Practical challenges

There are two practical issues involved. The first is that a large part of Anthropic’s workforce is not US citizens, and some of them have direct access to the source code for these models. 

But the potentially more daunting issue is that today it is difficult, if not impossible, to identify the citizenship of any AI user, which might force companies to assume that everyone might be unauthorized. 

In fact, said Yuri Goryunov, CIO of consulting firm Acceligence, “there is no way to check citizenship through an API call. Besides, three-quarters of Americans don’t have passports.”

Consultant Brian Levine, executive director of FormerGov, added that the issue will make life difficult for CIOs even if the Commerce position is viewed as dubious.

“Regardless of the strength of Commerce’s position, once it issues an ‘Is Informed’ letter, every unlicensed interaction with a foreign person becomes a potential violation, and the safest move is often to halt access until a licensing path exists,” he said.

This means that enterprise CIOs need to approach AI contracts with the knowledge that any government can now declare the product legally unavailable, with no notice. 

Sovereignty has climbed the stack

Howden said that this shift will force CIOs to strongly consider non-US AI models such as France’s Mistral or even China’s DeepSeek, “to reduce the concentration risk attached.” 

“There are hundreds out there that are very good. It is very easy to sit in the bubble of the four or five we know,” Howden said. “Enterprise CIOs think it’s a much more limited market than it really is.”

Sanchit Vir Gogia, chief analyst at Greyhound Research, said that enterprise executives now need to take the significant import rule changes into account when selecting AI models. 

“The harder truth is that sovereignty has climbed the stack,” he said. “The wall no longer stands around the database, it now stands around the intelligence layer itself. Under the export-control frame, it covers the release of controlled technology or source code to a foreign person, including one standing inside the United States. The border follows the person, not the parcel. Source code is part of the doctrine, but it is not the whole of it.”

He added, “the difficulty is that the cited rules speak of technology and source code, while the letter reaches for the model itself. A hosted model hands the user no weights and no code. It hands them inference, and inference is a capability, not a file.”

Ultimately, Gogia said, Anthropic’s decision to cut off model access to everyone immediately “was a rational answer to an impossible instruction. A frontier model can now vanish for reasons unconnected to uptime, price or performance. The same models that help secure systems can be withdrawn at the moment defenders most need them.”

This article originally appeared on CIO.com.

The technology, still far from clinical use, could one day prevent devastating diseases. But critics warn that even these early results may also fuel interest in commercial embryo editing, despite unresolved ethical and safety concerns.

Scientists at Columbia University have used a precise gene-editing tool, base editing, to make changes in three disease-linked genes in early-stage human embryos. The goal wasn’t to create pregnancies, but to test the safety and limits of rewriting DNA at the very early stages of life.

The paper, not yet peer reviewed, sparked immediate controversy. Some researchers hailed it as a technical milestone that could one day prevent devastating inherited diseases before birth. Others warned it edges society closer to the prospect of “designer babies”—an idea bioethicists have argued is akin to modern eugenics.

The debate is hardly hypothetical. The work has already attracted commercial interest. New York-based Nucleus Genomics, which screens in vitro fertilization (IVF) embryos for serious genetic disorders, has also developed predictive models for complex traits such as intelligence. The company plans to sponsor future research by study leader Dieter Egli and team.

Critics worry that even experimental advances could fuel demand from wealthy patients while encouraging companies to develop and market embryo-editing technologies, despite unresolved ethical and safety concerns.

Egli argues the findings should be public precisely because these debates are no longer academic curiosity. He has repeatedly called for scientists, regulators, and the public to weigh the pros and cons of editing human embryos. As for clinical use today, his position is unequivocal: “You can’t use it. It’s as clear as day and night,” he told Nature.

Conceptual Shift

Why edit embryos at all?

Cells in an early embryo eventually give rise to every tissue in the body. Correct a harmful mutation at the start of development, and the fix could, in theory, propagate throughout a child’s entire body—and even be passed on to future generations.

The strategy could help in genetic disorders that hamper fetal development or trigger diseases in newborns. For some developmental and metabolic conditions, intervention after birth may already be too late. Even when treatment is possible, gene editors must be able to target various organs, which is an ongoing challenge.

In various efforts, scientists have already repaired disease-causing mutations in mouse embryos and fetuses, including those linked to blood disorders. But mice aren’t humans. Early embryos from the two species repair DNA damage in fundamentally different ways, making it tough to gauge whether a strategy that works in mice will succeed, or prove safe, in people. That uncertainty has fueled interest in testing gene-editing tools directly in human embryos.

Not everyone is on board. International scientific groups have repeatedly called for a temporary ban on editing human embryos, and the practice is illegal in several countries.

That didn’t stop Chinese scientist He Jiankui. In 2018, he announced the birth of gene-edited babies after using a tool called CRISPR-Cas9, claiming the changes would protect them against HIV infection. Global outrage ensued.

By then, years of research had already highlighted CRISPR’s risk. The tool cuts both strands of DNA and relies on the body’s repair machinery to stitch them back together. But the process can go awry, introducing unintended mutations, deleting large chunks of DNA, or altering the wrong locations on the DNA strands altogether. He’s reckless experiment resulted in three years of imprisonment, although he still defends the work.

Subsequent studies only deepened concerns. In some cases, CRISPR editing in human embryos caused extensive genetic damage. In one study,  it completely destroyed the chromosome that housed the target gene.

An Imperfect Upgrade

The new study tested a next-generation gene editor designed to overcome some of CRISPR’s biggest shortcomings.

Egli and team used an approach called base editing, which rewrites individual DNA letters. Unlike CRISPR, base editing only nicks the DNA strands and is generally thought to be more precise. The technology hit a major milestone last year when it helped cure a baby with a potentially fatal genetic disorder, and earlier lab studies hinted it could also succeed in human embryos.

Working with early-stage embryos, the team edited three genes with the potential to cause illness. In each case, they converted the genetic letter A to G at precise locations. One of the genes, PCSK9, regulates “bad” cholesterol levels. Mutations are associated with a high risk of heart problems. The team’s edit was designed to switch off the gene, mirroring strategies already being explored in adults.

The other two targets, HBG1 and HBG2, control production of fetal hemoglobin, an oxygen-carrying protein. The edits made here reflected a natural protective variant that could lessen symptoms in blood disorders, such as sickle cell disease and beta thalassemia.

The team found no signs of widespread DNA damage, suggesting the tool is more precise than CRISPR. But it wasn’t perfect. Many embryos emerged as so-called genetic mosaics, with some cells carrying the intended edit and others retaining their original genetic blueprint.

That’s a huge problem. As an embryo develops, unedited cells could outcompete edited ones, leaving the disease-causing mutation largely intact. In some embryos, edited cells stopped dividing altogether.

And a lack of obvious chromosome damage doesn’t guarantee safety. The edits could still trigger harmful effects that aren’t noticeable until after birth—when it’s already too late to reverse them.

Calls for Scrutiny

Egli stresses that embryo editing is still far from being ready for the clinic. “These base editors—they can have damaging effects on the embryo. So why would you use it if you don’t fully understand that?” he told Nature.

His team is now working to reduce mosaicism and plans to test the technology in embryos that have developed to roughly 100 cells. This is when fertility clinics typically evaluate and freeze embryos.

Speaking to The New York Times, fertility expert Paula Amato at Oregon Health & Science University, who was not involved in the work, called the strategy “promising.” Genomics researcher Greg Neely at the University of Sydney in Australia also praised the work: “This will go down in history in a positive way—less reckless, more careful and ethical than previous attempts.”

Others remain deeply skeptical. Critics argue that embryo editing permanently alters the genetic inheritance of future generations, who have no say in the decision. The study’s ties to Nucleus Genomics also raised eyebrows. The company previously drew controversy for developing genetic predictions for traits such as intelligence and height and for its slogan “have your best baby.”

To Kian Sadeghi, CEO and cofounder of Nucleus, embryo editing extends that vision. The technology could help couples carrying mutations who struggle to produce enough unaffected embryos for selection during IVF.

Fyodor Urnov at the University of California, Berkeley, who was not involved in the study, isn’t convinced. IVF clinics already screen embryos for many inherited disorders without altering their DNA. Given the risks, selecting an unaffected embryo is often a safer option than rewriting its genome.

“In practical terms, therefore, this preprint will solely impact the rapidly growing movement of embryo editors for purposes of ‘baby improvement’,” he said.

That movement, once taboo, is gaining steam. Yet the traits most often cited by proponents—height, intelligence, emotional regulation—are shaped by hundreds or even thousands of genes, which scientists still don’t fully understand. Such enhancements are far beyond the reach of today’s technology. Every additional edit also increases the chance of unintended consequences.

For Egli, that’s precisely why the research should be discussed openly. “Research is necessary to provide information to discourage the wrong use of a technology,” he said.

The post Precise Gene Editing in Early Human Embryos Reignites the ‘Designer Baby’ Debate appeared first on SingularityHub.

Tipy (nejen) pro cestovatele, jak pozemní cestou autem nebo na motorce do Slovinska. Ceny, náklady, pokuty, rizika, tipy na úpory. Vše na jednom místě čistě z finančního pohledu.

Má nezletilé dítě nárok na odškodnění, když byla jeho podobizna bez souhlasu rodiče použita k propagaci nekomerční kulturní akce? Plakát s černošským chlapcem (mulatem) propagoval festival českých základních uměleckých škol. Soudy se musely  vypořádat i s otázkami rasismu.

V dalším článku ze světa operačního systému NuttX se podíváme na programování periferií jako jsou analogově-digitální převodník (ADC), pulzně šířková modulace (PWM) a ovládání vstupně-výstupních pinů (GPIO).

Ukážeme si některé možnosti, které integrovaný obvod POKEY nabízí pro generování zvuků: změnu vstupní frekvence zvukových kanálů, kanály se šestnáctibitovou děličkou, použití generátorů šumu i tvorbu efektu záznějů.

V květnu AMD ohlásila podporu FSR 4 (konkrétně tedy FSR 4.1) pro starší grafické architektury. Radeony RX 7000 ji přinesou již v červenci, ale Radeony RX 6000 až začátkem roku 2027. Již je znám důvod…

From August 3, 2026, Google will use IP addresses from UK, EEA and Switzerland users for ad measurement and personalization. It lands as the ICO weighs new consent rules, and years after Google itself called using such signals to identify devices "wrong." [...]

Researchers have uncovered a massive breach of Fortinet firewalls that has given Russian-speaking attackers near-unrestricted access to some of the world’s largest and most powerful organizations, including Oracle, Chevron, Lenovo, Federal Express, a NATO defense contractor, and Fortinet itself.

Nearly 74,000 Fortinet devices from more than 21,000 IP addresses in 194 countries have been compromised and their plaintext credentials exposed online, Bob Diachenko, a security researcher and head of SecurityDiscovery.com, said online and in an interview. He said he found the data after gaining access to the attackers’ command-and-control server and other infrastructure. The exposed data also included the industry, revenue, and employee count for each compromised organization.

Exceptional scale, poor opsec

Independent researcher Kevin Beaumont reported that “almost all” of the compromised devices remained online as of Wednesday morning. He went on to say that he has confirmed with multiple organizations found in the attackers’ logs that the credentials are real and current. In many cases, once the threat actors compromised the devices, they went on to access affected organizations’ centralized authentication systems, such as Radius servers and Microsoft Active Directory. The number of compromised devices comprises roughly half of all Internet-facing Fortinet firewalls, based on polling from Shodan.

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Tesco, a retail conglomerate headquartered in the United Kingdom, is moving 40,000 server workloads off of VMware amid "abusive conduct" from Broadcom, recent legal filings claim.

Tesco filed a lawsuit in the UK’s High Court against Broadcom alleging breach of contract last year. According to a September report from The Register, the lawsuit claimed that in January 2021, Tesco bought perpetual licenses for VMware’s vSphere Foundation and Cloud Foundation, a subscription to VMware Tanzu, plus support services until 2026, with the option to extend support for four additional years.

But when Broadcom took over VMware in November 2023, it would not honor the deal and instead tried to get Tesco to pay “excessive and inflated prices for virtualization software for which Tesco has already paid” and would not allow it to buy support services for its perpetually licensed software without buying “duplicative subscription-based licenses for those same Software products," the initial complaint read, The Register reported at the time.

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