Figma has issued a cease-and-desist letter to Swedish AI startup Loveable over the use of the term ‘Dev Mode,’ a name Figma trademarked in 2023.
Loveable recently introduced its own Dev Mode feature, prompting the design platform to demand the startup stop using the name, citing its established use and intellectual property rights.
Figma’s version of Dev Mode helps bridge the gap between designers and developers, while Loveable’s tool allows users to preview and edit code without linking to GitHub.
Despite their differing functions, Figma insists on protecting the trademark, even though ‘developer mode’ is a widely used phrase across many software platforms. Companies such as Atlassian and Wix have used similar terminology long before Figma obtained the trademark.
The legal move arrives as Figma prepares for an initial public offering, following Adobe’s failed acquisition attempt in 2023. The sudden emphasis on brand protection suggests the company is taking extra care with its intellectual assets ahead of its potential stock market debut.
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Taiwan Semiconductor Manufacturing Company (TSMC) posted a significant jump in quarterly profits, driven by robust demand for AI chips. Net income rose by just over 60% year-on-year to NT$360.7bn (£9.77bn), outpacing analysts’ expectations.
Revenue also grew by 41.6% compared to the same period in 2024, although it dipped slightly from the previous quarter due to weaker smartphone sales.
The world’s largest contract chipmaker has not yet seen any major changes in customer behaviour, including from Apple and Nvidia, despite increasing uncertainty over potential US tariffs on Taiwanese semiconductors.
While concerns about trade tensions grow, particularly with former President Donald Trump suggesting the US should reclaim chip production, TSMC says it is continuing with business as usual for now.
Instead of scaling back, TSMC is expanding its investment in the US, with plans to spend up to $160bn. Analysts believe this move could help the firm argue for a more favourable position should tariff negotiations intensify.
The company’s Chief Financial Officer, Wendell Huang, acknowledged the risks posed by changing trade policies but said revenue growth is still expected in the next quarter.
Despite global pressures, TSMC remains optimistic, forecasting revenue between $28.4bn and $29.2bn. Although the company’s shares have fallen more than 20% so far this year, some analysts say the stock is now undervalued and well-positioned to rebound once market conditions stabilise.
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Scammers are using fake mobile banking apps to trick people into handing over valuable items without receiving any payment.
These apps, which convincingly mimic legitimate platforms, display false ‘successful payment’ screens in person, allowing fraudsters to walk away with goods while the money never arrives.
Victims like Anthony Rudd and John Reddock have lost thousands after being targeted while selling items through social media marketplaces. Mr Rudd handed over £1,000 worth of tools from his Salisbury workshop, only to realise the payment notification was fake.
Mr Reddock, from the UK, lost a £2,000 gold bracelet he had hoped to sell to fund a holiday for his children.
BBC West Investigations found that some of these fake apps, previously removed from the Google Play store, are now being downloaded directly from the internet onto Android phones.
The Chartered Trading Standards Institute described this scam as an emerging threat, warning that in-person fraud is growing more complex instead of fading away.
With police often unable to track down suspects, small business owners like Sebastian Liberek have been left feeling helpless after being targeted repeatedly.
He has lost hundreds of pounds to fake transfers and believes scammers will continue striking, while enforcement remains limited and platforms fail to do enough to stop the spread of fraud.
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Spotify has resolved a global outage that left tens of thousands of users unable to stream music, with the company confirming the app is now ‘back up and functioning normally.’
The disruption, which began on Wednesday, affected search functions and artist pages, though downloaded music remained accessible during the issue.
The platform denied online rumours of a security breach, stating reports of a hack were ‘completely inaccurate.’
Users experienced timeout messages and errors when attempting to search for music, prompting frustration on social media, where many expressed disappointment and called for swift resolution.
With over 675 million users worldwide, Spotify’s brief downtime sparked threats from some users to switch to rival services such as Apple Music and YouTube.
The company responded on social media during the outage, acknowledging the problem and assuring users it was being investigated.
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Google has announced that Gemini Live’s screen and camera sharing capabilities will now be free for all Android users through the Gemini app.
The AI feature, which enables the app to interpret and respond to real-time visuals from a device’s screen or camera, had initially launched exclusively for Pixel 9 and Samsung Galaxy S25 users.
The company originally planned to restrict wider access to those subscribed to Gemini Advanced, but has now reversed that decision following strong user feedback. Google confirmed the broader rollout is beginning today and will continue over the coming weeks.
A promotional video released by the company demonstrates the feature in action, with a user pointing their phone camera at an aquarium while Gemini provides information about the marine life.
In a similar move, Microsoft has launched its own AI tool, Copilot Vision, for free via the Edge browser.
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OpenAI has introduced a new monitoring system to reduce the risk of its latest AI models, o3 and o4-mini, being misused to create chemical or biological threats.
The ‘safety-focused reasoning monitor’ is built to detect prompts related to dangerous materials and instruct the AI models to withhold potentially harmful advice, instead of providing answers that could aid bad actors.
These newer models represent a major leap in capability compared to previous versions, especially in their ability to respond to prompts about biological weapons. To counteract this, OpenAI’s internal red teams spent 1,000 hours identifying unsafe interactions.
Simulated tests showed the safety monitor successfully blocked 98.7% of risky prompts, although OpenAI admits the system does not account for users trying again with different wording, a gap still covered by human oversight instead of relying solely on automation.
Despite assurances that neither o3 nor o4-mini meets OpenAI’s ‘high risk’ threshold, the company acknowledges these models are more effective at answering dangerous questions than earlier ones like o1 and GPT-4.
Similar monitoring tools are also being used to block harmful image generation in other models, yet critics argue OpenAI should do more.
Concerns have been raised over rushed testing timelines and the lack of a safety report for GPT-4.1, which was launched this week instead of being accompanied by transparency documentation.
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AMD has warned that new US government restrictions on exporting AI chips to China and several other countries could materially affect its earnings.
The company said it may face charges of up to $800 million related to unsold inventory, purchase commitments, and reserves if it fails to secure export licences for its MI308 GPUs, now subject to strict control measures.
In a filing to the US Securities and Exchange Commission, AMD confirmed it would seek the necessary licences but admitted there is no guarantee they will be granted.
The move follows broader export restrictions aimed at protecting national security interests, with US officials arguing that unrestricted access to advanced chips would weaken the country’s strategic lead in AI, instead of preserving it.
AMD’s stock dropped around 6% following the announcement. Competitors are also feeling the impact. Nvidia expects charges of $5.5 billion from similar restrictions, and Intel’s Gaudi hardware line has reportedly been affected as well.
The US Commerce Department has defended the move as necessary to safeguard economic and national interests.
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Elon Musk’s AI venture, xAI, has introduced a new ‘memory’ feature for its Grok chatbot in a bid to compete more closely with established rivals like ChatGPT and Google’s Gemini.
The update allows Grok to remember details from past conversations, enabling it to provide more personalised responses when asked for advice or recommendations, instead of offering generic answers.
Unlike before, Grok can now ‘learn’ a user’s preferences over time, provided it’s used frequently enough. The move mirrors similar features from competitors, with ChatGPT already referencing full chat histories and Gemini using persistent memory to shape its replies.
According to xAI, the memory is fully transparent. Users can view what Grok has remembered and choose to delete specific entries at any time.
The memory function is currently available in beta on Grok’s website and mobile apps, although not yet accessible to users in the EU or UK.
Instead of being automatically enabled, it can be turned off in the settings menu under Data Controls. Deleting individual memories is also possible via the web chat interface, with Android support expected shortly.
xAI has confirmed it is working on adding memory support to Grok’s version on X. However, this expansion aims to deepen the bot’s integration with users’ digital lives instead of limiting the experience to one platform.
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South Korean researchers have discovered a way to generate much stronger spin currents at room temperature, potentially transforming the future of electronics.
By using a mechanism called longitudinal spin pumping and a special iron-rhodium material, the team showed that quantum magnetisation dynamics, once thought to only occur at extremely low temperatures, can take place in everyday conditions.
These currents were found to be 10 times stronger than those created through traditional methods, offering a major boost for low-power, high-performance devices.
Instead of relying on the movement of electric charge, spintronics makes use of the electron’s spin, which reduces energy loss and heat generation. This advancement could be particularly beneficial for Magnetoresistive Random Access Memory (MRAM), a type of memory that depends on spin currents to function.
Researchers believe their findings may significantly cut power consumption in MRAM, which is already being explored by companies like Samsung for next-generation AI computing systems.
The study, carried out by teams at KAIST and Sogang University, used a combination of ultrafast measurement experiments and theoretical analysis to validate the discovery. Experts say the results could lead to a new era of energy-efficient memory and processor technologies.
Instead of stopping here, the researchers now plan to develop novel spintronic device architectures and explore other quantum-based mechanisms to push the limits of what modern electronics can achieve.
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Microsoft researchers have introduced the largest 1-bit AI model to date, called BitNet b1.58 2B4T, designed to run efficiently on standard CPUs instead of relying on GPUs. This ‘bitnet’ model, now openly available under the MIT license, can even operate on Apple’s M2 chips.
Bitnets use extreme weight quantisation, storing only -1, 0, or 1 as values, making them far more memory- and compute-efficient than most conventional models.
With 2 billion parameters and trained on 4 trillion tokens, roughly the equivalent of 33 million books, BitNet b1.58 2B4T outperforms several similarly sized models in key benchmarks.
Microsoft claims it beats Meta’s Llama 3.2 1B, Google’s Gemma 3 1B, and Alibaba’s Qwen 2.5 1.5B on tasks like grade-school maths and physical reasoning. It also runs up to twice as fast while using significantly less memory, offering a potential edge for lower-end or energy-constrained devices.
The main limitation lies in its dependence on Microsoft’s custom bitnet.cpp framework, which supports only select hardware and does not yet work with GPUs.
Instead of being broadly compatible with existing AI systems, BitNet’s performance depends on a narrower infrastructure, a hurdle that may limit adoption, despite its promise for lightweight AI deployment.
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