Technology

An old proverb famously states, "If you want to go fast, go alone. If you want to go far, go together."

This is especially true when it comes to artificial intelligence, where breakneck advances happen seemingly every day. And while individual companies are rapidly fielding their own AI-powered chatbots and analysis tools, real long-term improvement and innovation in this new scientific frontier often requires broad collaboration in developing open and trusted AI systems that produce accurate, reliable, and safe outputs.

Early conventional wisdom held that only so-called 'closed' AI systems controlled by one company could be safe and trusted. Some argued that open models would inevitably undermine safety or lead to misuse. But experience is quickly showing that open source models and the collaboration they bring are a powerful tool for promoting security and trust.

The power of collaboration

Collaboration is a powerful force for AI advancement because it fosters diverse perspectives and capabilities. When it comes to AI, collaboration can, in many cases, be optimized by leveraging open source to reduce bias, increase transparency, gain greater control over our data, and ultimately, accelerate time to innovation.

According to McKinsey, organizations that view AI as essential to their competitive advantage are far more likely to use open source AI models and tools than organizations that do not. Open source AI models, tools, and frameworks enable developers and researchers to build upon existing work, rather than starting from scratch, to achieve higher-quality outputs more quickly.

The open source software approach thrives on community contributions, bringing together individuals, companies, and organizations from around the globe to collaborate on shared goals. This is where organizations like the AI Alliance—which was spearheaded by IBM and others, and is comprised of technology creators, developers, and adopters collaborating to advance safe and responsible AI—play a crucial role.

By pooling resources and knowledge, the AI Alliance provides a platform for sharing and developing AI innovations. This meritocracy yields immediate value, both for the broader technology ecosystem and the world at large.

Why the AI Alliance matters today

There are many practical and ethical reasons for such broad-based AI partnerships. AI research and development require substantial resources, including data, computing power, and expertise. The availability of open source models keeps costs down, broadening choices and helping to prevent the concentration of the AI industry in the hands of a few major players.

The AI Alliance also offers a forum to hold honest conversations among like-minded organizations about AI-related legislation and its impacts on greater innovation and adoption.

In a short time, the AI Alliance has blossomed into a vibrant ecosystem, bringing together a critical mass of data, tools, and talent. Today, more than 140 organizational members from 23 countries collaborate through the alliance to address some of the most pressing challenges in AI.

Open source is particularly critical to members of the alliance, including Databricks, which has long championed the democratization of AI. We’ve open sourced many critical big data processing and analytics projects, like the Delta Lake, MLflow, and Unity Catalog tools that underpin many large data and AI deployments today.

When it comes to today’s AI ecosystem, we need to ensure that everyone, including academics, researchers, non-profits, and beyond, can access and understand the best AI tools and models. The more we all understand these models and how to utilize them, the more we can share ideas on how to safely shape the future of AI and subsequently use it to solve today’s toughest challenges.

But we can’t do it alone.

Collaborate, code, and create the future of AI

We established a policy working group within the Alliance to focus not only on advocacy but also on developing responses to government requests that could impact open-source AI development. For example, last year, we contributed to the landmark National Telecommunications and Information Administration study examining potential benefits and risks of open weight frontier AI models.

The final NTIA report strongly underscored the valuable role of open models in today’s AI ecosystem, while also highlighting the need for vigilant monitoring and ongoing evaluation of policies to manage emerging risks in the future.

Our intention is to ensure that AI regulation is thoughtfully crafted so that open source AI thrives. Organizations like the AI Alliance have laid a solid foundation for international cooperation, but it's just the beginning.

If you work at a business that prioritizes artificial intelligence, you too can be part of this important work. Start by developing educational programs, workshops, and training sessions – and joining AI-related projects and communities – to share knowledge and build tools that benefit others.

You can create and share your own open source projects, such as datasets, pre-trained models, or utilities, which build on a foundation of AI fairness, transparency, and accessibility to ensure the benefits of AI are widely distributed. Check out GitHub or Hugging Face to look for AI/ML projects that align with your skills and interests.

The advent of AI is a pivotal moment in our collective human history. Experience shows that collaboration will be key to our success in advancing AI innovation with safety and trust. We must move into this promising future with open arms and open software models and tools, adequately prepared for the challenges ahead. Let's go far—together.

We list the best IT Automation software.

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

Here are hints and the answers for the NYT Connections: Sports Edition puzzle for Aug. 11, No. 322

Here are the answers for The New York Times Mini Crossword for Aug. 11

Here are hints and answers for the NYT Strands puzzle for Aug. 11, No. 526.

Here are some hints and the answers for the NYT Connections puzzle for Aug. 11, #792.

Here are hints and the answer for today's Wordle for Aug. 11, No. 1,514

• Experts warn a single calendar entry can silently hijack your smart home without your knowledge
• Researchers proved AI can be hacked to control smart homes using only words
• Saying “thanks” triggered Gemini to switch on the lights and boil water automatically

The promise of AI-integrated homes has long included convenience, automation, and efficiency, however, a new study from researchers at Tel Aviv University has exposed a more unsettling reality.

In what may be the first known real-world example of a successful AI prompt-injection attack, the team manipulated a Gemini-powered smart home using nothing more than a compromised Google Calendar entry.

The attack exploited Gemini’s integration with the entire Google ecosystem, particularly its ability to access calendar events, interpret natural language prompts, and control connected smart devices.

From scheduling to sabotage: exploiting everyday AI access

Gemini, though limited in autonomy, has enough “agentic capabilities” to execute commands on smart home systems.

That connectivity became a liability when the researchers inserted malicious instructions into a calendar appointment, masked as a regular event.

When the user later asked Gemini to summarize their schedule, it inadvertently triggered the hidden instructions.

The embedded command included instructions for Gemini to act as a Google Home agent, lying dormant until a common phrase like “thanks” or “sure” was typed by the user.

At that point, Gemini activated smart devices such as lights, shutters, and even a boiler, none of which the user had authorized at that moment.

These delayed triggers were particularly effective in bypassing existing defenses and confusing the source of the actions.

This method, dubbed “promptware,” raises serious concerns about how AI interfaces interpret user input and external data.

The researchers argue that such prompt-injection attacks represent a growing class of threats that blend social engineering with automation.

They demonstrated that this technique could go far beyond controlling devices.

It could also be used to delete appointments, send spam, or open malicious websites, steps that could lead directly to identity theft or malware infection.

The research team coordinated with Google to disclose the vulnerability, and in response, the company accelerated the rollout of new protections against prompt-injection attacks, including added scrutiny for calendar events and extra confirmations for sensitive actions.

Still, questions remain about how scalable these fixes are, especially as Gemini and other AI systems gain more control over personal data and devices.

Unfortunately, traditional security suites and firewall protection are not designed for this kind of attack vector.

To stay safe, users should limit what AI tools and assistants like Gemini can access, especially calendars and smart home controls.

Also, avoid storing sensitive or complex instructions in calendar events, and don’t allow AI to act on them without oversight.

Be alert to unusual behavior from smart devices and disconnect access if anything seems off.

Via Wired

You might also like

• Microsoft urges users to be on alert following high-severity flaw in hybrid Exchange deployments
• Here's a list of the best firewalls around today
• These are the best endpoint security tools right now

• 3D printers built complex concrete parts faster, yet long-term durability remains largely untested
• Oak Ridge finished reactor shielding in days, raising speed-versus-safety debates across the industry
• Advanced construction methods rely more on software, reducing labor yet increasing system dependence

In East Tennessee, a 3D printer arm has been used to build concrete shielding columns for a nuclear reactor.

The work is part of the Hermes Low-Power Demonstration Reactor project, supported by the US Department of Energy, and marks a new direction in how nuclear infrastructure is built, with both 3D printing and AI tools playing major roles.

And according to Oak Ridge National Laboratory (ORNL), large parts of the construction were completed in just 14 days, which could have taken several weeks using conventional methods.

Efficiency gains clash with engineering caution

The new method uses 3D printers to create detailed molds for casting concrete, even in complex shapes, with the goal of making construction faster, cheaper, and more flexible while relying more on US-based materials and labor.

AI tools also played a role in the project, as ORNL used the technology to guide parts of the design and building process.

These tools may help reduce human error and speed up work, especially when creating difficult or unique parts, but depending heavily on AI also raises questions. How can builders be sure these systems won’t make unnoticed mistakes? Who checks the decisions that are automated?

The project is also a response to rising energy demands - as AI systems and data centers use more power, nuclear energy is seen as a stable source to support them.

Some experts say that future AI tools may end up running on power from reactors they helped design, a feedback loop that could be both efficient and risky.

The use of 3D printing in this project makes it possible to build precise structures faster.

Still, it’s not yet clear how well these 3D-printed parts will hold up over time.

Nuclear reactors need to last for decades, and failure in any part of the structure could be dangerous. Testing and quality checks must keep up with the speed of new building methods.

For now, 3D printing and AI seem to offer powerful tools for the nuclear industry.

But while faster construction is a major benefit, safety must remain the top concern - this “new era” may bring improvements, but it will need close attention and caution at every step.

Via Toms Hardware

You might also like

• These are the best business laptops available to buy right now
• And you should take a look at the best office chairs we've tried
• Google says hackers stole some of its data following Salesforce breach

Resistance bands are a home workout staple that can help you strengthen and tone a variety of muscles. Our experts have found the top options worth adding to your exercise routine.

• More Pixel Watch 4 information has leaked
• We can see new sensors and charging contacts
• The wearable should launch on August 20

The Pixel Watch 4 is almost certainly going to be unveiled alongside the Pixel 10 series and the Pixel Buds 2a on Wednesday, August 20 – though Google has only confirmed the date, not what's being launched – and a new leak gives us more information on the wearable.

Images posted to Reddit (via 9to5Google) show what look to be official marketing slides for the Pixel Watch 4, detailing features such as improved durability, battery life, and activity tracking accuracy – courtesy of a "Gen 3 sensor hub".

That would be an upgrade on the sensors we saw with the Google Pixel Watch 3, and should mean better precision in readings such as heart rate – though we won't know for sure until we've actually had an opportunity to try it out.

We also get another look at the rather unusual side charging system that showed up in an earlier leak, with charge contacts positioned on the side of the watch casing: it would appear this is how you'll be able to charge up the Pixel Watch 4.

'Technological advancements'

The Pixel Watch 3 was launched in August 2024 (Image credit: Google)

There's plenty of positive phrasing in these marketing materials, as you would expect. The watch apparently brings "significant technological advancements" over its predecessor, together with a "premium crafted design".

The battery life is listed as reaching 30 hours between charges, which is said to be a 25% boost over the current model. Better battery life had already been mentioned in previous leaks, so we're hopeful in that particular department.

There's also mention of the two expected watch sizes, 41 mm and 42 mm, while Gemini integration is mentioned, as well as "dual frequency" GPS – which suggests the wearable will be more accurate and faster in reporting its location.

Together with the rest of the leaked information that's also emerged in recent days, it looks as though the Pixel Watch 4 could be an appealing prospect, when it's finally confirmed – and perhaps worth a spot on our best smartwatches list.

You might also like

• The Pixel Watch 4 could improve repairability
• These are the best Android smartwatches
• You may have to wait to buy the Pixel Watch 4

The European giants face off at Signal Iduna Park in both teams' final warmup match before the start of their new campaigns.

The Foxes begin their campaign against an Owls team in crisis.

Enzo Maresca's Blues wrap up their preseason preparations with a home clash against the Rossoneri.

The season curtain-raiser at Wembley sees the EPL champions take on the cup-winning Eagles.

Looking for speedy internet in DC? Good news -- you can pick from many reliable ISPs. Here are our top picks.

I learned a few portable AC quirks in my first year of ownership to help you decide if one of these compact coolers is right for your home.

• OpenAI’s new models run efficiently on minimal hardware, but haven’t been independently tested for workloads
• The models are designed for edge use cases where full-scale infrastructure isn’t always available
• Apache 2.0 licensing may encourage broader experimentation in regions with strict data requirements

OpenAI has released two open-weight models, gpt-oss-120B and gpt-oss-20B, positioning them as direct challengers to offerings like DeepSeek-R1 and other large language learning models (LLMs) currently shaping the AI ecosystem.

These models are now available on AWS through its Amazon Bedrock and Amazon SageMaker AI platforms.

This marks OpenAI’s entry into the open-weight model segment, a space that until now has been dominated by competitors such as Mistral AI and Meta.

OpenAI and AWS

The gpt-oss-120B model runs on a single 80 GB GPU, while the 20B version targets edge environments with only 16 GB of memory required.

OpenAI claims both models deliver strong reasoning performance, matching or exceeding its o4-mini model on key benchmarks.

However, external evaluations are not yet available, leaving actual performance across varied workloads open to scrutiny.

What distinguishes these models is not only their size, but also the license.

Released under Apache 2.0, they are intended to lower access barriers and support broader AI development, particularly in high-security or resource-limited environments.

According to OpenAI, this move aligns with its broader mission to make artificial intelligence tools more widely usable across industries and geographies.

On AWS, the models are integrated into enterprise infrastructure via Amazon Bedrock AgentCore, enabling the creation of AI agents capable of performing complex workflows.

OpenAI suggests these models are suitable for tasks like code generation, scientific reasoning, and multi-step problem-solving, especially where adjustable reasoning and chain-of-thought outputs are required.

Their 128K context window also supports longer interactions, such as document analysis or technical support tasks.

The models also integrate with developer tooling, supporting platforms like vLLM, llama.cpp, and Hugging Face.

With features like Guardrails and upcoming support for custom model import and knowledge bases, OpenAI and AWS are pitching this as a developer-ready foundation for building scalable AI applications.

Still, the release feels partly strategic, positioning OpenAI as a key player in open model infrastructure, while also tethering its technology more closely to Amazon Web Services, a dominant force in cloud computing.

You might also like

• These are the best business laptops available to buy right now
• And you should take a look at the best office chairs we've tried
• Microsoft Teams and Zoom can be hijacked to give hackers the keys to your kingdom

Prime Video's library is packed with sci-fi gold.

Monster season 4: key information

- Yet to be officially confirmed by Netflix
- Will follow the story of Lizzie Borden
- Whole new cast expected
- No official trailer released yet
- No news on future seasons

Monster season 4 is coming, though the news is yet to be officially confirmed. The true crime anthology series has become a record breaker for Netflix, one of the best streaming services, as season 1 reached one billion hours of viewing in its first 60 days. Monster being one of only four series to have achieved this.

Unsurprisingly, all focus is currently on the upcoming season 3, reportedly dropping on the streamer in October. Season 3 will focus on Ed Gein's story, played by Charlie Hunnam. But, there's still plenty to say about season 4. Such as, how it will turn its attention to Lizzie Borden – an entirely different tale with the show's first female lead.

So, here's what we know so far about the next (next) instalment of Monster from the potential release date, possible cast, news, rumors and more.

Monster season 4: is there a release date?

Jeffrey Dahmer was the focus on Monster season 1 (Image credit: Netflix)

No, there's not a release date for Monster season 4 just yet, but that's not surprising since season 3 is yet to stream on Netflix.

But, according to What's On Netflix?, creator Ryan Murphy revealed that season 3 is slated to drop in October.

And, for Monster season 4, Variety confirmed (although Netflix hasn't yet) that it is "already in the works" and is "currently prepping for a potential fall shoot".

With seasons 1 and 2 released in September, season 3 with a supposed October release date, I'd predict we won't see season 4 until September/October 2026.

Monster season 4: has a trailer been released?

Season 2 was called 'Monsters' focusing on the Menendez brothers (Image credit: Netflix)

There's no Monster season 4 trailer to share just yet and that's because filming hasn't even commenced. With production rumored to begin in fall, I'd expect we won't see a trailer until late 2026 in line with the predicted release date.

Monster season 4: predicted cast

A new cast for each season of Monster (Image credit: Netflix)

With each season of the anthology series following a different true crime story, the cast is always entirely new. So, when it comes to predicting the Monster season 4 cast, it's almost impossible.

What we do know is that each season of Monster so far has starred big names in the lead roles. For season 1, Evan Peters was Jeffrey Dahmer. For season 2, the Menendez brothers were played by Cooper Koch and Nicholas Alexander Chavez.

And, as confirmed by Tudum, season 3 will see Charlie Hunnam play Ed Gein with supporting cast Laurie Metcalf, Tom Hollander and Olivia Williams.

For Monster season 4 then, there will be a female lead to play Lizzie Borden. But, who that is, we'll have to wait and see. I'll be sure to update here as soon as I hear more about the casting for this season.

Monster season 4: story synopsis and rumors

It's not the first time Lizzie's tale has been told (Image credit: Lifetime)

Full spoilers for Monster seasons 1 to 3 to follow.

Netflix's Monster depicts true crime stories with each season following a different case. For season 1, it was Jeffrey Dahmer. For season 2, Lyle and Erik Menendez. And for the upcoming season 3, Ed Gein.

And it has already been revealed that Monster season 4 will tell the story of Lizzie Borden. Her life and crimes though are a little different than the three seasons that came before. As the first female lead, Lizzie Borden was actually tried and acquitted for the axe murders of her father and stepmother in 1892.

Now, if you've not heard of Lizzie Borden before, a quick internet search will no doubt give you all the information you need and thus, the plot of Monster season 4. But, in the interest of not ruining the entire season, I won't delve into all the details here.

It's not the first time Lizzie's tale has been told though, which is not entirely surprising considering how prolific a case it was for its time. There's 2015's The Lizzie Borden Chronicles, which saw Christina Ricci in the titular role. Or, 2018's Lizzie with Chloë Sevigny.

For Monster season 4 being a true crime retelling of the story, I imagine it'll be as tense and thrilling as the seasons that came before it.

Will there be more seasons of Monster?

Lizzie now, but who next? (Image credit: Roadside Attractions)

There's a few reasons why it's hard to speculate on future seasons of Monster, namely that season 3's release date is yet to be confirmed and secondly, while season 4 is reportedly happening, there's actually been no official word from Netflix... yet.

So, with this in mind, it seems unlikely we'll hear about any future seasons of Monster anytime soon. But, as such a resounding success on the streaming platform and with an abundance of prolific true crime stories left to tell, there's always hope that Monster will continue for many more seasons to come.

For more Netflix-based coverage, read our guides to Nobody Wants This season 2, Stranger Things season 5, The Four Seasons season 2, and One Piece season 2.

• Phishing attacks now bypass multi-factor authentication using real-time digital wallet provisioning tactics
• One-time passcodes are no longer enough to stop fraudsters with mobile-optimized phishing kits
• Millions of victims were targeted using everyday alerts like tolls, packages, and account notices

A wave of advanced phishing campaigns, traced to Chinese-speaking cybercriminal syndicates, may have compromised up to 115 million US payment cards in just over a year, experts have warned.

Researchers at SecAlliance revealed these operations represent a growing convergence of social engineering, real-time authentication bypasses, and phishing infrastructure designed to scale.

Investigators have identified a figure referred to as “Lao Wang” as the original creator of a now widely adopted platform that facilitates mobile-based credential harvesting.

Identity theft scaled through mobile compromise

At the center of the campaigns are phishing kits distributed through a Telegram channel known as “dy-tongbu,” which has rapidly gained traction among attackers.

These kits are designed to avoid detection by researchers and platforms alike, using geofencing, IP blocks, and mobile-device targeting.

This level of technical control allows phishing pages to reach intended targets while actively excluding traffic that might flag the operation.

The phishing attacks typically begin with SMS, iMessage, or RCS messages using everyday scenarios, such as toll payment alerts or package delivery updates, to drive victims toward fake verification pages.

There, users are prompted to enter sensitive personal information, followed by payment card data.

The sites are often mobile-optimized to align with the devices that will receive one-time password (OTP) codes, allowing for immediate multi-factor authentication bypass.

These credentials are provisioned into digital wallets on devices controlled by attackers, allowing them to bypass additional verification steps normally required for card-not-present transactions.

Researchers described this shift to digital wallet abuse as a “fundamental” change in card fraud methodology.

It enables unauthorized use at physical terminals, online shops, and even ATMs without requiring the physical card.

Researchers have observed criminal networks now moving beyond smishing campaigns.

There is growing evidence of fake ecommerce sites and even fake brokerage platforms being used to collect credentials from unsuspecting users engaged in real transactions.

The operation has grown to include monetization layers, including pre-loaded devices, fake merchant accounts, and paid ad placements on platforms like Google and Meta.

As card issuers and banks look for ways to defend against these evolving threats, standard security suites, firewall protection, and SMS filters may offer limited help given the precision targeting involved.

Given the covert nature of these smishing campaigns, there is no single public database listing affected cards. However, individuals can take the following steps to assess possible exposure:

• Review recent transactions
• Look for unexpected digital wallet activity
• Monitor for verification or OTP requests you didn’t initiate
• Check if your data appears in breach notification services
• Enable transaction alerts

Unfortunately, millions of users may remain unaware their data has been exploited for large-scale identity theft and financial fraud, facilitated not through traditional breaches.

Via Infosecurity

You might also like

• Ex-Huawei semiconductor secret thieves sentenced to jail
• Here's a list of the best firewalls around today
• These are the best endpoint security tools right now