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President Trump's executive order extends a reprieve from the threat of rising tariffs between the world's two largest economies.

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• Ryan Reynolds has hinted that he'll appear in one or both of the next two Avengers movies
• The Deadpool star sent fans into a frenzy with a cryptic Instagram post
• The image and caption features call-backs to two of the most profitable Marvel films

Another day, another Avengers: Doomsday cast rumor – but, this time, it's a Marvel actor who's whipped fans into a frenzy over a possible appearance in the film.

Taking to Instagram overnight, Deadpool star Ryan Reynolds sparked a frenzied reaction from fans about his potential inclusion in the superhero flick.

A post shared by Ryan Reynolds (@vancityreynolds)

A photo posted by on

Ordinarily, a post like this wouldn't be much to write home about. The image, which features a red, rebel-style version of the Avengers logo on top of the superteam's official emblem, might be viewed as nothing more than a call-back to Deadpool and Wolverine. That's the only Marvel Cinematic Universe (MCU) movie that launched in theaters last year, and it ended up making over $1 billion globally.

It's the caption accompanying said image that's excited MCU fans, though. Referencing a key line of dialog uttered by Clint Barton/Hawkeye in 2019's Avengers: Endgame, Reynolds wrote: "Don't do that. Don't give me hope".

The implication here, of course, is that Reynolds is suggesting The Merc With a Mouth could finally get his wish to join Earth's Mightiest Heroes to combat an otherworldly threat. Deadpool says as much in Deadpool and Wolverine's first act when he interviews for a place on the super-group's roster.

Reynolds wasn't part of Doomsday's initial 27-strong cast that was announced via a four-hour livestream in March. Less than 24 hours later, though, Marvel insisted "there's always room for more", thereby indicating that more cast additions might be made in the months ahead. If you're interested, here's a list of 17 other Marvel heroes I'd like to see in Avengers: Doomsday.

But I digress. Reynolds' latest social media post insinuates Deadpool will appear in a future Avengers movie, but I'm not sure he'll show up in Avengers 5. I think he'd serve a better purpose by being a big part of Avengers: Secret Wars instead.

Deadpool has already traversed the Marvel multiverse multiple times (Image credit: Marvel Studios)

Hear me out first. As I outlined in my Deadpool and Wolverine ending explained piece, the movie ends with the titular pair residing on Earth-10005. That's the parallel universe – one of many that exists alongside Earth-616, aka the MCU – that the bulk of the MCU Phase 5 film is set in.

Furthermore, Joe and Anthony Russo, who returned to the MCU to helm Doomsday and its sequel, told me that they're "drawing inspiration" from both of Marvel's 'Secret Wars' comic book series. I won't spoil the events of either literary works here – you can learn more about how they may influence Doomsday and its follow-up in the aforementioned linked-to article and my Fantastic Four: First Steps ending explained piece. The latter article reveals how the first Marvel Phase 6 movie might set up Doomsday's plot, so it's also worth reading.

Anyway, considering what's likely to happen in Doomsday (seriously, read the two articles linked above), it makes more sense for Deadpool to meet The Avengers in Secret Wars rather than shoehorn him into its predecessor. Doomsday is already going to be a busy film with so many characters in it. As I pointed out above, more heroes could be part of proceedings, so Marvel might be best served delaying Deadpool's team-up with The Avengers until Secret Wars to ensure the emotional pay-off – for the character and fans alike – is worth the wait.

But, what do you think? Has Reynolds all but confirmed Deadpool will appear in either or both Avengers movies? Which one would you prefer to see him in? Let me know in the comments. Then, check out my dedicated guide on Avengers: Doomsday for the latest news and rumors on the highly anticipated flick.

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• Thomas Dohmke resigns as GitHub CEO, effective by the end of 2025
• GitHub is getting closer to Microsoft as it aligns with CoreAI business
• Microsoft CEO says "internal organizational boundaries are meaningless" anyway

GitHub CEO Thomas Dohmke has announced he is resigning as CEO of the company as Microsoft begins to bring GitHub closer to its CoreAI team.

Following the move, Microsoft will not appoint a new GitHub CEO and the company will no longer have a single leader, instead reporting more directly into its CoreAI division.

After a four-year stint, Dohmke will continue to serve as CEO until the end of 2025, however he has alluded to plans to found a new startup.

GitHub CEO resigns, no new CEO in sight

CoreAI, led by former Meta exec Jay Parikh, is Microsoft's new division for building AI platforms and tools.

"GitHub and its leadership team will continue its mission as part of Microsoft’s CoreAI organization," Dohmke wrote.

The departing CEO also noted "pride in everything we’ve built as a remote-first organization" – it was recently revealed Microsoft could be looking to increase its in-office working days, and it's unclear whether Dohmke's comment is a secret dig at this.

With GitHub set to become more closely aligned with Microsoft's CoreAI, we could speculate that the developer platform's workers could be affected by any upcoming changes.

Speaking about the scale of GitHub, Dohmke mentioned that the platform now houses over one billion repos and forks, more than 150 million developers, and more recently, over 20 million Copilot users.

"By launching this new age of developer AI, we’ve made it possible for anyone – no matter what language they speak at home or how fluent they are in programming – to take their spark of creativity and transform it into something real," he added.

When Satya Nadella launched CoreAI, he explained that besides bringing together "Dev Div, AI Platform and some key teams from the Office of the CTO (AI Supercomputer, AI Agentic Runtimes, and Engineering Thrive)," it would also "build out GitHub Copilot" – an early clue that the popular developer platform would be losing some of its independence.

Nadella also noted: "We must remember that our internal organizational boundaries are meaningless to both our customers and to our competitors."

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• iOS 26 beta 6 is out for developers
• There are changes to Liquid Glass and the Camera app
• There are also 7 new ringtones

Apple continues to push out beta updates for its iOS 26 software ahead of a full launch later this year, and the latest beta 6 version for developers brings with it a number of interesting tweaks – including one I'm particularly keen to try out.

As reported by TechCrunch and others, iOS 26 is snappier than ever, with app launching and switching noticeably faster – a sure sign that Apple is continuing to optimize the software before it gets rolled out to millions of iPhones.

There are also more tweaks to Liquid Glass here (via MacRumors), with more transparency on the lock screen, and a more 3D look to the lock-screen clock. Apple also seems to have done more work to improve text legibility with the Liquid Glass effect.

Apple has also brought back the previous swipe direction for the modes on the Camera screen, so it's very much as you were with that – a couple of betas ago it reversed the swipe direction for some unknown reason, which messed up the muscle memory of the majority of users.

Added ringtones

iOS 26 beta 6 adds 6 new ringtones!All 6 are variants of “Reflection” pic.twitter.com/BN3mWXm2t5August 11, 2025

There's also a new and improved onboarding process for users here, which will help explain all the changes when iOS 26 rolls out to the masses (most likely in September, with the iPhone 17 series). Do note though that this is the developer beta, and you won't see these changes yet if you're in the public beta program.

What I'm most excited about, however, are the seven new ringtones Apple has added, giving you even more choice for incoming calls. As well as some neat variations on the default Reflection ringtone, there's also a brand-new one called Little Bird.

I've already given it a listen, and it's a jaunty number that mixes synth and whistling sounds to interesting effect. I also like the new Reflection takes, which sound familiar, but which each have a fresh new sound layered on top.

I may be opening myself up to ridicule by getting excited about new ringtones, but these are sounds I hear every day, and new ones are always welcome – it's actually been a couple of years now since Apple treated us to any new variations.

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Awdah Al Hathaleen was shot during a clash with an Israeli settler. His West Bank village hoped No Other Land, the Oscar-winning film about settler violence that he worked on, might help protect them.

(Image credit: Tamir Kalifa)

• The malicious group VexTrio Viper developed and shared a host of fake apps via legit app stores, new research reveals
• Malicious applications include VPNs, ad-blockers, RAM cleaners, and even online dating services
• VexTrio Viper employs traffic distribution systems (TDSs) to spread malware and other online scams since at least 2015

No matter if you download your VPN app through Google Play or Apple App Store, there's still a chance it could be a malicious app developed by VexTrio Viper.

In an extensive report, researchers at Infoblox Threat Intel revealed how the fraudulent adtech group published a range of applications on official app stores – from virtual private network (VPN) and ad-blockers to RAM cleaners and even online dating services.

Thought to be active since 2015, VexTrio is a complex criminal enterprise that involves several companies and employs traffic distribution systems (TDSs) to spread malware and other online scams.

At least seven security apps impacted

"They released apps under several developer names, including HolaCode, LocoMind, Hugmi, Klover Group, and AlphaScale Media. [...] Available in the Google Play and Apple stores, these have been downloaded millions of times in aggregate," Infoblox explained to The Hacker News.

Specifically, at least seven applications supposed to offer security tools have been developed by LocoMind, which in 2024 claimed over 500,000 downloads and 50,000 active users for their apps.

These include various VPN services, such as Fast VPN - Super Proxy, and other utility applications, like RAM cleaners.

Once users have installed these applications on their devices, they are bombarded with intrusive ads and prompted to sign up for deceptive subscriptions.

(Image credit: APKPure)

The team at Infoblox Threat Intel has tracked VexTrio's malicious activities since 2022, publishing various reports throughout the years.

Among these, in June 2025, researchers disclosed a criminal web between WordPress hackers and a traffic distribution system (TDS) operated by the VexTrio group.

In 2024, they also unveiled VexTrio's massive malicious affiliate program that worked like a food delivery service for criminals.

"In total, the VexTrio enterprise includes nearly a hundred companies and brands. The scope of their activities includes malicious apps and large-scale spamming operations, and as we published a few months ago, they have a special relationship with numerous website hackers," notes researchers.

How to stay safe

This story is a stark reminder that it isn't enough for an application to be on an official app store to be safe. You should be even more careful when it comes to a security tool, as cybercriminals are notorious for taking advantage of unprotected devices.

For instance, in April, an investigation found at least 20 free VPN apps with undisclosed Chinese ownership lurking in Apple's official app store in the US. At least five of these were linked with a Shanghai-based firm believed to have ties with the Chinese military.

While the best VPN services boost your online anonymity and security by encrypting your internet traffic and spoofing your IP address, malicious apps pose risks to your privacy.

As a rule of thumb, you should only download a reliable service with a strong no-log VPN policy and a history of independent third-party audits.

If you aren't willing to pay for a premium service just yet, I recommend checking Proton VPN and Privado VPN, as they currently are the best free VPNs on the market, according to TechRadar's reviewers.

That said, our testing confirmed NordVPN as the best all-arounder right now, thanks to great security/privacy features and impeccable performance. Even better, perhaps, you may still be in time to grab TechRadar's exclusive deal, which expires on August 12, 2025.

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Some residents are skeptical President Trump's use of tough police tactics will work to solve complex social ills.

(Image credit: Win McNamee)

AOL debuted the service in 1991. Dial-up has largely been replaced by broadband internet.

(Image credit: Mark Lennihan)

Dredging waterways for navigation is a centuries-old practice, but this project is controversial because the mud being dug out of the channel is put into other parts of Mobile Bay.

(Image credit: Blake Jones for NPR)

Imagine a health plan member interacting with their insurer’s virtual assistant, typing, “I just lost my mom and feel overwhelmed.” A conventional chatbot might respond with a perfunctory “I’m sorry to hear that” and send a list of FAQs. This might be why 59% of chatbot users before 2020 felt that “the technologies have misunderstood the nuances of human dialogue.”

In contrast, an AI agent can pause, offer empathetic condolences, gently guide the member to relevant resources, and even help schedule an appointment with their doctor. This empathy, paired with personalization, drives better outcomes.

When people feel understood, they’re more likely to engage, follow through, and trust the system guiding them. Oftentimes in regulated industries that handle sensitive topics, simple task automation fails when users abandon engagements that feel rigid, incompetent, or lack understanding of the individual’s circumstances.

AI agents can listen, understand, and respond with compassion. This combination of contextual awareness and sentiment‑driven response is more than just a nice‑to‑have add-on—it’s foundational for building trust, maintaining engagement, and ensuring members navigating difficult moments get the personalized support they need.

Beyond Automation: Why Empathy Matters in Complex Conversations

Traditional automation excels at straightforward, rule‑based tasks but struggles when conversations turn sensitive. AI agents, by contrast, can detect emotional cues—analyzing tone, punctuation, word choice, conversation history, and more—and deliver supportive, context‑appropriate guidance.

This shift from transactional to relational interactions matters in regulated industries, where people may need help navigating housing assistance, substance-use treatment, or reproductive health concerns.

AI agents that are context-aware and emotionally intelligent can support these conversations by remaining neutral, non‑judgmental, and attuned to the user’s needs.

They also offer a level of accuracy and consistency that’s hard to match—helping ensure members receive timely, personalized guidance and reliable access to resources, which could lead to better, more trusted outcomes.

The Technology Under the Hood

Recent advances in large language models (LLMs) and transformer architectures (GPT‑style models) have been pivotal to enabling more natural, emotionally aware conversations between AI agents and users. Unlike early sentiment analysis tools that only classified text as positive or negative, modern LLMs predict word sequences across entire dialogues, effectively learning the subtleties of human expression.

Consider a scenario where a user types, “I just got laid off and need to talk to someone about my coverage.” An early-generation chatbot might respond with “I can help you with your benefits,” ignoring the user’s distress.

Today’s emotionally intelligent AI agent first acknowledges the emotional weight: “I’m sorry to hear that—losing a job can be really tough.” It then transitions into assistance: “Let’s review your coverage options together, and I can help you schedule a call if you'd like to speak with someone directly."

These advances bring two key strengths. First, contextual awareness means AI agents can track conversation history—remembering what a user mentioned in an earlier exchange and following up appropriately.

Second, built‑in sentiment sensitivity allows these models to move beyond simple positive versus negative tagging. By learning emotional patterns from real‑world conversations, these AI agents can recognize shifts in tone and tailor responses to match the user’s emotional state.

Ethically responsible online platforms embed a robust framework of guardrails to ensure safe, compliant, and trustworthy AI interactions. In regulated environments, this includes proactive content filtering, privacy protections, and strict boundaries that prevent AI from offering unauthorized advice.

Sensitive topics are handled with predefined responses and escalated to human professionals when needed. These safeguards mitigate risk, reinforce user trust, and ensure automation remains accountable, ethical, and aligned with regulatory standards.

Navigating Challenges in Regulated Environments

For people to trust AI in regulated sectors, AI must do more than sound empathetic. It must be transparent, respect user boundaries, and know when to escalate to live experts. Robust safety layers mitigate risk and reinforce trust.

Empathy Subjectivity

Tone, cultural norms, and even punctuation can shift perception. Robust testing across demographics, languages, and use cases is critical. When agents detect confusion or frustration, escalation paths to live agents must be seamless, ensuring swift resolution and access to the appropriate level of human support when automated responses may fall short.

Regulatory Compliance and Transparency

Industries under strict oversight cannot allow hallucinations or unauthorized advice. Platforms must enforce transparent disclosures—ensuring virtual agents identify themselves as non-human—and embed compliance‑driven guardrails that block unapproved recommendations. Redirects to human experts should be fully logged, auditable, and aligned with applicable frameworks.

Guardrail Management

Guardrails must filter hate speech or explicit content while distinguishing between abusive language and expressions of frustration. When users use mild profanity to convey emotional distress, AI agents should recognize the intent without mirroring the language—responding appropriately and remaining within company guidelines and industry regulations.

Also, crisis‑intervention messaging—responding to instances of self‑harm, domestic violence, or substance abuse—must be flexible enough for organizations to tailor responses to their communities, connect people with local resources, and deliver support that is both empathetic and compliant with regulatory standards.

Empathy as a Competitive Advantage

As regulated industries embrace AI agents, the conversation is shifting from evaluating their potential to implementing them at scale. Tomorrow’s leaders won’t just pilot emotion‑aware agents but embed empathy into every customer journey, from onboarding to crisis support.

By committing to this ongoing evolution, businesses can turn compliance requirements into opportunities for deeper connection and redefine what it means to serve customers in complex, regulated environments.

Regulated AI must engineer empathy in every interaction. When systems understand the emotional context (not just data points), they become partners rather than tools. But without vertical specialization and real-time guardrails, even the most well-intentioned AI agents can misstep.

The future belongs to agentic, emotionally intelligent platforms that can adapt on the fly, safeguard compliance, and lead with compassion when it matters most. Empathy, when operationalized safely, becomes more than a UX goal—it becomes a business advantage.

We list the best enterprise messaging platform.

This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

Vacuum cleaners divide opinion more than you might expect, and the brand that people seem to feel most strongly about is Dyson. Behind every diehard Dyson fan there are 10 more people ready to eagerly proclaim that they're the worst vacuums in the world.

At the weekend, designer Mike Smith proclaimed on X that Dyson vacuums were "not for serious vacuumers" and the ensuing thread went viral, with over 1,000 people piling in to air their vacuum views.

My hot take is that Dyson vacuums are not for serious vacuumers.Battery is garbage, filter is garbage. Canister too small. Absolute joke of a cleaning tool.August 10, 2025

I manage the vacuum cleaner content for TechRadar, which includes reviewing vacs from many different brands and putting together our official best vacuum cleaner ranking. All of that means I spend far more time than the average person thinking about vacuum cleaners.

I'm neither wildly pro- or anti-Dyson, and this discussion didn't sway me any further in either direction. What it did do is make me even more confident in my long-held belief that what most people actually have a problem with is not Dyson vacuums, but cordless stick vacuums in general.

Cordless stick vacuums are not the same as traditional upright vacuums or canister vacs. In some ways, they're worse. Providing strong suction requires a lot of power, and the bigger the battery the heavier the vacuum – so brands are constantly trying to balance whether to provide customers with longer runtimes or a lighter build.

A bigger dust cup means a vacuum that's bulkier and heavier, so there's another trade-off there in terms of how often you have to empty it. They also seem to be an inherently less robust type of cleaner – cordless stick vacs are expected to have a far shorter overall lifespan than other styles of vacuum.

(Image credit: Future)

In short, if you choose a cordless stick vacuum, you should expect limited runtimes on higher suction modes, canisters that need emptying regularly, and for it not to last forever. For those compromises, you get something you don't need to plug into the wall, and which you can easily use to vacuum up the stairs – or even on the ceiling – if you want to.

Of course, some cordless vacs perform much better than others, but broadly speaking you should expect those pros and cons to be true whatever model or brand you go for. Dyson stick vacs might not be for "serious" vacuuming, but boy are they good for convenient, comfortable vacuuming.

(Of course, the other element when it comes to Dyson is the price. I get into this more in my article exploring if Dyson vacuums are worth it, and I've also written about by experience of Shark vs Dyson vacuums, if you're interested in that comparison specifically.)

In the thread, the name that crops up again and again from the opposing chorus is Miele. This brand is synonymous with canister vacuums, and not a direct comparison. One of the very best vacuums I've used in terms of outright suction power remains the 25+ year-old upright that used to belong to my Nana and now lives in my parents' house. But it weighs a ton and takes up a load of space, so when it comes to cleaning my own flat, I'd reach for a Dyson (or similar) every time.

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Al Jazeera's Anas al-Sharif and five of his colleagues at the network were killed in an Israeli airstrike targeting Gaza's most recognized television journalist.

(Image credit: Anas Baba)

Trump said Ukrainian President Volodymyr Zelenskyy was unlikely to be included in talks he described as a "feel out meeting" to better understand Russia's demands for ending its war in Ukraine.

(Image credit: Aurelien Morissard, left and center, Pavel Bednyakov, right)

Artificial Intelligence (AI) is rapidly reshaping the landscape of fraud prevention, creating new opportunities for defense as well as new avenues for deception.

Across industries, AI has become a double-edged sword. On one hand, it enables more sophisticated fraud detection, but on the other, it is being weaponized by threat actors to exploit controls, create synthetic identities and launch hyper-realistic attacks.

Fraud prevention is vital in sectors handling high volumes of sensitive transactions and digital identities. In financial services, for example, it's not just about protecting capital - regulatory compliance and customer trust are at stake.

Similar cybersecurity pressures are growing in telecoms and tech industries like SaaS, ecommerce and cloud infrastructure, where threats like SIM swapping, API abuse and synthetic users can cause serious disruption.

Fraud has already shifted from a risk to a core business challenge - with 58 per cent of key decision-makers in large UK businesses now viewing it as a ‘serious threat’, according to a survey conducted in 2024.

The rise of synthetic threats

Synthetic fraud refers to attacks that leverage fabricated data, AI-generated content or manipulated digital identities. These aren’t new concepts, but the capability and accessibility of generative AI tools have dramatically lowered the barrier to entry.

A major threat is the creation of synthetic identities which are combinations of real and fictitious information used to open accounts, bypass Know-Your-Customer (KYC) checks or access services.

Deepfakes are also being used to impersonate executives during video calls or in phishing attempts. One recent example involved attackers using AI to mimic a CEO’s voice and authorize a fraudulent transfer. These tactics are difficult to detect in fast-moving digital environments without advanced, real-time verification methods.

Data silos only exacerbate the problem. In many tech organizations, different departments rely on disconnected tools or platforms. One team may use AI for authentication while another still relies on legacy systems, and it is these blind spots which are easily exploited by AI-driven fraud.

AI as a defense

While AI enables fraud, it also offers powerful tools for defense if implemented strategically. At its best, AI can process vast volumes of data in real time, detect suspicious patterns and adapt as threats evolve. But this depends on effective integration, governance and oversight.

One common weakness lies in fragmented systems. Fraud prevention efforts often operate in silos across compliance, cybersecurity and customer teams. To build true resilience, organizations must align AI strategies across departments. Shared data lakes, or secure APIs, can enable integrated models with a holistic view of user behavior.

Synthetic data, often associated with fraud, can also play a role in defense. Organizations can use anonymized, realistic data to simulate rare fraud scenarios and train models without compromising customer privacy. This approach helps test defenses against edge cases not found in historical data.

Fraud systems must also be adaptive. Static rules and rarely updated models can’t keep pace with AI-powered fraud - real-time, continuously learning systems are now essential. Many companies are adopting behavioral biometrics, where AI monitors how users interact with devices, such as typing rhythm or mouse movement, to detect anomalies, even when credentials appear valid.

Explainability is another cornerstone of responsible AI use and it is essential to understand why a system has flagged or blocked activity. Explainable AI (XAI) frameworks help make decisions transparently, supporting trust and regulatory compliance, ensuring AI is not just effective, but also accountable.

Industry collaboration

AI-enhanced fraud doesn’t respect organizational boundaries, and as a result, cross-industry collaboration is becoming increasingly important. While sectors like financial services have long benefited from information-sharing frameworks like ISACs, similar initiatives are emerging in the broader tech ecosystem.

Cloud providers are beginning to share indicators of compromised credentials or coordinated malicious activity with clients. SaaS and cybersecurity vendors are also forming consortiums and joint research initiatives to accelerate detection and improve response times across the board.

Despite its power, AI is not a silver bullet and organizations which rely solely on automation risk missing subtle or novel fraud techniques. Effective fraud strategies should include regular model audits, scenario testing and red-teaming exercises (where ethical hackers conduct simulated cyberattacks on an organization to test cybersecurity effectiveness).

Human analysts bring domain knowledge and judgement that can refine model performance. Training teams to work alongside AI is key to building synthetic resilience, combining human insight with machine speed and scale.

Resilience is a system, not a feature

As AI transforms both the tools of fraud and the methods of prevention, organizations must redefine resilience. It’s no longer about isolated tools, but about creating a connected, adaptive, and explainable defense ecosystem.

For many organizations, that means integrating AI across business units, embracing synthetic data, prioritizing explainability, and embedding continuous improvement into fraud models. While financial services may have pioneered many of these practices, the broader tech industry now faces the same level of sophistication in fraud, and must respond accordingly.

In this new era, synthetic resilience is not a static end goal but a capability to be constantly cultivated. Those who succeed will not only defend their businesses more effectively but help define the future of secure, AI-enabled digital trust.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

Insulin needles. Sleeping bags. Nutella. These are items Arwa Damon’s charity — International Network for Aid, Relief and Assistance — has tried to send to Gaza and Israel has rejected. It’s a glimpse into the harsh reality of a humanitarian crisis with no end in sight. Today on the show, we talk to Damon about the economics of running a humanitarian nonprofit and what’s stopping more aid from reaching Gaza. 

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For sponsor-free episodes of The Indicator from Planet Money, subscribe to Planet Money+ via Apple Podcasts or at plus.npr.org. 

Fact-checking by Sierra Juarez. Music by Drop Electric. Find us: TikTok, Instagram, Facebook, Newsletter. 

(Image credit: Mohammed Abed)

A Chinese scientist, He Jiankui, made a shocking announcement to the world in 2018: He had secretly engineered the birth of the first gene-edited babies. The birth of the twins was seen as reckless and unethical by the scientific community. That’s because, among other things, the CRISPR gene-editing technique Jiankui used was so new. NPR science correspondent Rob Stein has been following the controversial world of gene-editing and human reproduction, including some companies’ recent quests to push gene-editing technology forward.

Read more of Rob Stein’s reporting on the topic here.

Interested in more science news? Let us know at shortwave@npr.org. 

Listen to every episode of Short Wave sponsor-free and support our work at NPR by signing up for Short Wave+ at plus.npr.org/shortwave.

(Image credit: jm1366)

The landscape of smart data capture software is undergoing a significant transformation, with advancements that can help businesses build long-term resilience against disruptions like trade tariffs, labor shortages, and volatile demand.

No longer confined to handheld computers and mobile devices, the technology is embracing a new batch of hybrid data capture methods that include fixed cameras, drones, and wearables.

If you weren’t familiar with smart data capture, it is the ability to capture data intelligently from barcodes, text, IDs, and objects. It enables real-time decision-making, engagement, and workflow automation at scale across industries such as retail, supply chain, logistics, travel, and healthcare.

The advancements it’s currently experiencing are beyond technological novelties; they are further redefining how businesses operate, driving ROI, enhancing customer experience, and streamlining operational workflows. Let’s explore how:

More than just smartphones

Traditionally, smart data capture relied heavily on smartphones and handheld computers, devices that both captured data and facilitated user action. With advancements in technology, the device landscape is expanding. Wearables like smart glasses and headsets, fixed cameras, drones, and even robots are becoming more commonplace, each with its own value.

This diversification leads to the distinction of devices that purely ‘capture’ data versus those that can ‘act’ on it too. For example, stationary cameras or drones capture data from the real world and then feed it into a system of record to be aggregated with other data.

Other devices — often mobile or wearable — can capture data and empower users to act on that information instantly, such as a store associate who scans a shelf and can instantly be informed of a pricing error on a particular item. Depending on factors such as the frequency of data collected, these devices can allow enterprises to tailor a data capture strategy to their needs.

Practical innovations with real ROI

In a market saturated with emerging technologies, it's easy to get caught up in the hype of the next big thing. However, not all innovations are ready for prime time, and many fail to deliver a tangible return on investment, especially at scale. The key for businesses is to focus on practical, easy-to-implement solutions that enhance workflows rather than disrupt them by leveraging existing technologies and IT infrastructure.

An illustrative example of this evolution is the increasing use of fixed cameras in conjunction with mobile devices for shelf auditing and monitoring in retail environments. Retailers are deploying mobile devices and fixed cameras to monitor shelves in near real-time and identify out-of-stock items, pricing errors, and planogram discrepancies, freeing up store associates’ time and increasing revenue — game-changing capabilities in the current volatile trade environment, which triggers frequent price changes and inventory challenges.

This hybrid shelf management approach allows businesses to scale operations no matter the store format: retailers can easily pilot the solution using their existing mobile devices with minimal upfront investment and assess all the expected ROI and benefits before committing to full-scale implementation.

The combination also enables further operational efficiency, with fixed cameras providing continuous and fully automated shelf monitoring in high-footfall areas, while mobile devices can handle lower-frequency monitoring in less-frequented aisles.

This is how a leading European grocery chain increased revenue by 2% in just six months — an enormous uplift in a tight-margin vertical like grocery.

Multi-device and multi-signal systems

An important aspect of this data capture evolution is the seamless integration of all these various devices and technologies. User interfaces are being developed to facilitate multi-device interactions, ensuring that data captured by one system can be acted upon through another.

For example, fixed cameras might continuously monitor inventory levels, with alerts to replenish specific low-stock items sent directly to a worker's wearable device for immediate and hands-free action.

And speaking of hands-free operation: gesture recognition and voice input are also becoming increasingly important, especially for wearable devices lacking traditional touchscreens. Advancing these technologies would enable workers to interact with items naturally and efficiently.

Adaptive user interfaces also play a vital role, ensuring consistent experiences across different devices and form factors. Whether using a smartphone, tablet, or digital eyewear, the user interface should adapt to provide the necessary functionality without a steep learning curve; otherwise, it may negatively impact the adoption rate of the data capture solution.

Recognizing the benefits, a large US grocer implemented a pre-built adaptive UI to enable top-performing scanning capabilities on existing apps to 100 stores in just 90 days.

The co-pilot system

As the volume of data increases, so does the potential for information overload. In some cases, systems can generate thousands of alerts daily, overwhelming staff and hindering productivity. To combat this, businesses are adopting so-called co-pilot systems — a combination of devices and advanced smart data capture that can guide workers to prioritize ROI-optimizing tasks.

This combination leverages machine learning to analyze sales numbers, inventory levels, and other critical metrics, providing frontline workers with actionable insights. By focusing on high-priority tasks, employees can work more efficiently without sifting through endless lists of alerts.

Preparing for the future

As the smart data capture landscape continues to evolve and disruption becomes the “new normal”, businesses must ensure their technology stacks are flexible, adaptable, and scalable.

Supporting various devices, integrating multiple data signals, and providing clear task prioritization are essential for staying competitive in an increasingly complex, changeable and data-driven market.

By embracing hybrid smart data capture device strategies, businesses can optimize processes, enhance user experiences, and make informed decisions based on real-time data.

The convergence of mobile devices, fixed cameras, wearables, drones, and advanced user interfaces represents not just an evolution in technology but a revolution in how businesses operate. And in a world where data is king, those who capture it effectively — and act on it intelligently — will lock in higher margins today and lead the way tomorrow.

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The Trump administration has pressured China to have the Hong Kong-based operator of ports at either end of the canal sell those interests to a U.S. consortium.

(Image credit: Matias Delacroix)

Miguel Uribe was shot three times while giving a campaign speech in a park and had since remained in an intensive care unit in serious condition with episodes of slight improvement.

(Image credit: Fernando Vergara)

Google Gemini introduced a new feature aimed at education called Guided Learning this month. The idea is to teach you something through question-centered conversation instead of a lecture.

When you ask it to teach you something, it breaks the topic down and starts asking you questions about it. Based on your answers, it explains more details and asks another question. The feature provides visuals, quizzes, and even embeds YouTube videos to help you absorb knowledge.

As a test, I asked Gemini's Socratic tutor to teach me all about cheese. It started by asking me about what I think is in cheese, clarifying my somewhat vague answer with more details, and then asking if I knew how those ingredients become cheese. Soon, I was in a full-blown cheese seminar. For every answer I gave, Gemini came back with more details or, in a gentle way, told me I was wrong.

The AI then got into cheese history. It framed the history as a story of traveling herders, clay pots, ancient salt, and Egyptian tombs with cheese residue. It showed a visual timeline and said, “Which of these surprises you most?” I said the tombs did, and it said, “Right? They found cheese in a tomb and it had survived.” Which is horrifying and also makes me respect cheese on a deeper level.

In about 15 minutes, I knew all about curds and whey, the history of a few regional cheese traditions, and even how to pick out the best examples of different cheeses. I could see photos in some cases and a video tour of a cellar full of expensive wheels of cheese in France. The AI quizzed me when I asked it to make sure I was getting it, and I scored a ten out of ten.

(Image credit: Gemini screenshots)Cheesemonger AI

It didn’t feel like studying, exactly. More like falling into a conversation where the other person knows everything about dairy and is excited to bring you along for the ride. After learning about casein micelles. starter cultures, and cutting the curd, Gemini asked me if I wanted to learn how to make cheese.

I said sure, and it guided me through the process of making ricotta, including pictures to help show what it should look like at each step.

(Image credit: Gemini screenshots)

By the time I was done with that part of the conversation, I felt like I’d taken a mini‑course in cheesemaking. I'm not sure I am ready to fill an entire cheeseboard or age a wheel of gruyère in my basement.

Still, I think making ricotta or maybe paneer would be a fun activity in the next few weeks. And I can show off a mild, wobbly ball of dairy pride thanks to learning from questioning, and, as it were, being guided to an education.

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