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AMD warns of financial hit from US AI chip export ban

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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xAI pushes Grok forward with memory update

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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Quantum spin breakthrough at room temperature

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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Hamburg Declaration champions responsible AI

The Hamburg Declaration on Responsible AI for the Sustainable Development Goals (SDGs) is a new global initiative jointly launched by the United Nations Development Programme (UNDP) and Germany’s Federal Ministry for Economic Cooperation and Development (BMZ).

The Declaration seeks to build a shared vision for AI that supports fair, inclusive, and sustainable global development. It is set to be officially adopted at the Hamburg Sustainability Conference in June 2025.

The initiative brings together voices from across sectors—governments, civil society, academia, and industry—to shape how AI can ethically and effectively align with the SDGs. Central to this effort is an open consultation process inviting stakeholders to provide feedback on the draft declaration, participate in expert discussions, and endorse its principles.

In addition to the declaration itself, the initiative also features the AI SDG Compendium, a global registry of AI projects contributing to sustainable development. The process has already gained visibility at major international forums like the Internet Governance Forum and the AI Action Summit in Paris, reflecting its growing significance in leveraging responsible AI for the SDGs.

The Declaration aims to ensure that AI is developed and used in ways that respect human rights, reduce inequalities, and foster sustainable progress. Establishing shared principles and promoting collaboration across sectors and regions sets a foundation for responsible AI that serves both people and the planet.

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Microsoft unveils powerful lightweight AI model for CPUs

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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Google uses AI and human reviews to fight ad fraud

Google has revealed it suspended 39.2 million advertiser accounts in 2024, more than triple the number from the previous year, as part of its latest push to combat ad fraud.

The tech giant said it is now able to block most bad actors before they even run an advert, thanks to advanced large language models and detection signals such as fake business details and fraudulent payments.

Instead of relying solely on AI, a team of over 100 experts from across Google and DeepMind also reviews deepfake scams and develops targeted countermeasures.

The company rolled out more than 50 LLM-based safety updates last year and introduced over 30 changes to advertising and publishing policies. These efforts, alongside other technical reinforcements, led to a 90% drop in reports of deepfake ads.

While the US saw the highest number of suspensions, with all 39.2 million accounts coming from there alone, India followed with 2.9 million accounts taken down. In both countries, ads were removed for violations such as trademark abuse, misleading personalisation, and financial service scams.

Overall, Google blocked 5.1 billion ads globally and restricted another 9.1 billion, instead of allowing harmful content to spread unchecked. Nearly half a billion of those removed were linked specifically to scam activity.

In a year when half the global population headed to the polls, Google also verified over 8,900 election advertisers and took down 10.7 million political ads.

While the scale of suspensions may raise concerns about fairness, Google said human reviews are included in the appeals process.

The company acknowledged previous confusion over enforcement clarity and is now updating its messaging to ensure advertisers understand the reasons behind account actions more clearly.

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Inephany raises $2.2M to make AI training more efficient

London-based AI startup Inephany has secured $2.2 million in pre-seed funding to develop technology aimed at making the training of neural networks—particularly large language models—more efficient and affordable.

The investment round was led by Amadeus Capital Partners, with participation from Sure Valley Ventures and AI pioneer Professor Steve Young, who joins as both chair and angel investor.

Founded in July 2024 by Dr John Torr, Hami Bahraynian, and Maurice von Sturm, Inephany is building an AI-driven platform that improves training efficiency in real time.

By increasing sample efficiency and reducing computing demands, the company hopes to dramatically cut the cost and time of training cutting-edge models.

The team claims their solution could make AI model development at least ten times more cost-effective compared to current methods.

The funding will support growth of Inephany’s engineering team and accelerate the launch of its first product later this year.

With the costs of training state-of-the-art models now reaching into the hundreds of millions, the startup’s platform aims to make high-performance AI development more sustainable and accessible across industries such as healthcare, weather forecasting, and drug discovery.

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South Korea’s $23B chip industry boost in response to global trade war

South Korea announced a $23 billion support package for its semiconductor industry, increasing from last year’s $19 billion to protect giants like Samsung and SK Hynix from US tariff uncertainties and China’s growing competition.

The plan allocates 20 trillion won in financial aid, up from 17 trillion, to drive innovation and production, addressing a 31.8% drop in chip exports to China due to US trade restrictions.

The package responds to US policies under President Trump, including export curbs on high-bandwidth chips to China, which have disrupted global demand.

At the same time, Finance Minister Choi Sang-mok will negotiate with the US to mitigate potential national security probes on chip trade.

South Korea’s strategy aims to safeguard a critical economic sector that powers everything from smartphones to AI, especially as its auto industry faces US tariff challenges.

Analysts view this as a preemptive effort to shield the chip industry from escalating global trade tensions.

Why does it matter?

For South Koreans, the semiconductor sector is a national lifeline, tied to jobs and economic stability, with the government betting big to preserve its global tech dominance. As China’s tech ambitions grow and US policies remain unpredictable, Seoul’s $23 billion investment speaks out about the cost of staying competitive in a tech-driven world.

Nvidia hit by the new US export rules

Nvidia is facing fresh US export restrictions on its H20 AI chips, dealing a blow to the company’s operations in China.

In a filing on Tuesday, Nvidia revealed it now needs a licence to export these chips indefinitely, after the US government cited concerns they could be used in a Chinese supercomputer.

The company expects a $5.5 billion charge linked to the controls in its first fiscal quarter of 2026, which ends on 27 April. Shares dropped around 6% in after-hours trading.

The H20 is currently the most advanced AI chip Nvidia can sell to China under existing regulations.

Last week, reports suggested CEO Jensen Huang might have temporarily eased tensions during a dinner at Donald Trump’s Mar-a-Lago resort, by promising investments in US-based AI data centres instead of opposing the rules directly.

Just a day before the filing, Nvidia announced plans to manufacture some chips in the US over the next four years, though the specifics were left vague.

Calls for tighter controls had been building, especially after it emerged that China’s DeepSeek used the H20 to train its R1 model, a system that surprised the US AI sector earlier this year.

Government officials had pushed for action, saying the chip’s capabilities posed a strategic risk. Nvidia declined to comment on the new restrictions.

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Quantum breakthrough could be just years away

Most quantum professionals believe that quantum utility — the point at which quantum computers outperform classical machines in solving real-world problems — could be reached within the next decade.

According to a new survey by Economist Impact, 83% of global experts expect quantum utility to arrive in ten years or less, with one-third predicting it will happen in as little as one to five years.

Optimism aligns with some industry roadmaps, such as Finnish startup IQM, which is targeting quantum utility as early as next year.

However, there’s still little consensus on the timeline. While Google’s CEO Sundar Pichai recently suggested practically useful quantum computers could be five to ten years away, Nvidia’s Jensen Huang believes it may take at least 15 years — a remark that briefly shook confidence in quantum stocks.

Industry confusion over terms like ‘quantum utility,’ ‘advantage,’ and ‘supremacy’ only adds to the uncertainty, highlighting the need for clearer communication and better public understanding.

Despite the buzz, major challenges remain. Over 80% of professionals cite technical barriers, especially error correction, as a major hurdle.

A further 75% point to a lack of skilled talent in the field. While misconceptions about quantum computing are seen as slowing progress, the real bottlenecks lie in engineering and workforce development.

If these can be overcome, quantum computing could revolutionise sectors from pharmaceuticals and materials science to finance and cybersecurity — with profound implications, both promising and perilous.

For more information on these topics, visit diplomacy.edu.