AI assistants deliver answers in seconds, but the process behind the scenes, called inference, is complex. Inference lets trained AI models generate responses, recommendations, or images, accounting for up to 90% of AI computing power.
AWS has built infrastructure to handle these fast, high-volume operations reliably and efficiently.
Inference involves four main stages: tokenisation, prefill, decoding, and detokenisation. Each step converts human input into machine-readable tokens, builds context, generates responses token by token, and converts output back to readable text.
AWS custom Trainium chips speed up the process while reducing costs. AI agents add complexity by chaining multiple inferences for multi-step tasks.
AWS uses its Bedrock platform, Project Mantle engine, and Journal tool to manage long-running requests, prioritise urgent tasks, and maintain low latency. Unified networking ensures efficiency and fairness across users.
By focusing on inference-first infrastructure, AWS lowers AI costs while enabling more advanced applications. Instant responses from AI assistants are the result of years of engineering, billions in investment, and systems built to scale globally.
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Swiss lender PostFinance has broadened its digital-asset offering to 22 cryptocurrencies, adding Algorand, Arbitrum, NEARProtocol, Stellar, USDC, and Sui to its platform. The expansion strengthens its position as one of the most comprehensive retail crypto offerings among Swiss banks.
Direct cryptocurrency access was introduced in early 2024, making the institution the first systemically important bank in Switzerland to provide such services. Further additions followed mid-year, reflecting growing client demand for regulated exposure to digital assets.
More than 36,000 custody accounts have been opened since launch, generating over 565,000 trades. According to Alexander Thoma, the bank continues to broaden its selection as customers increasingly prefer to manage crypto through their primary banking provider.
Trading is available via e-finance and the PostFinance app, with a minimum entry level of $50 for both savings plans and individual orders, a move aimed at lowering barriers and widening retail participation.
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A fresh analysis from Arthur Hayes argues that Bitcoin is signalling mounting stress in the global fiat system as it diverges from the Nasdaq 100. Hayes says Bitcoin is the most sensitive market gauge of credit supply, making its decoupling a possible early warning of systemic stress.
He links the risk to accelerating AI-driven layoffs among knowledge workers. Data cited from CBS News shows firms attributed roughly 55,000 job cuts in 2025 to AI adoption, a sharp rise from two years earlier.
A significant drop in employment, he argues, could translate into large mortgage and consumer-credit losses for US banks.
Estimates suggest a 20% drop in US knowledge workers could trigger about $557 billion in credit losses, hitting bank capital and regional lenders first. Hayes expects instability to force the Federal Reserve to add liquidity, a move he says could lift Bitcoin to new highs.
Beyond the flagship cryptocurrency, Hayes said his firm Maelstrom may allocate stablecoin reserves to Zcash and Hyperliquid once monetary policy shifts, although timing and price targets remain unspecified.
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Dutch lawmakers have approved a new tax law that will impose a 36% levy on actual investment returns, including both realised and unrealised gains from cryptocurrencies such as Bitcoin and Ethereum.
The law, called the Actual Return in Box 3 Act, takes effect on 1 January 2028 and applies annually, meaning investors will owe tax even if assets are not sold.
Real estate and startup shares are exempt from mark-to-market taxation, raising concern among crypto investors. Critics say taxing paper gains may force investors to sell assets or consider moving to more favourable jurisdictions.
The government defended the measure as essential to prevent significant revenue losses.
The legislation includes some relief measures, such as a tax-free annual return for small savers and unlimited loss carry-forward above certain thresholds, allowing investors to offset downturns against future gains.
Despite these provisions, many crypto advocates argue that taxing unrealised gains remains problematic.
Crypto adoption in the Netherlands is growing rapidly. Indirect holdings by Dutch companies, institutions, and households reached $1.42 billion by October 2025, up from $96 million in 2020.
Officials say the long-term goal is to move towards a realised gains model, but annual taxation of paper gains is currently seen as necessary to safeguard public finances.
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Meta announced a multiyear partnership with NVIDIA to build large-scale AI infrastructure across on-premises and cloud systems. Plans include hyperscale data centres designed for both training and inference workloads, forming a core part of the company’s long-term AI roadmap.
Deployment will include millions of Blackwell and Rubin GPUs, plus expanded use of NVIDIA CPUs and Spectrum-X networking. According to Mark Zuckerberg, the collaboration is intended to support advanced AI systems and broaden access to high-performance computing capabilities worldwide.
Jensen Huang highlighted the scale of Meta’s AI operations and the role of deep hardware-software integration in improving performance.
Efficiency gains remain a central objective, with Meta increasing the rollout of Arm-based NVIDIA Grace CPUs to improve performance per watt in data centres. Future Vera CPU deployment is being considered to expand energy-efficient computing later in the decade.
Privacy-focused AI development forms another pillar of the partnership. NVIDIA Confidential Computing will first power secure AI features on WhatsApp, with plans to expand across more services as Meta scales AI to billions of users.
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Mortgage lenders face growing pressure to govern AI as regulatory uncertainty persists across the United States. States and federal authorities continue to contest oversight, but accountability for how AI is used in underwriting, servicing, marketing, and fraud detection already rests with lenders.
Effective AI risk management requires more than policy statements. Mortgage lenders need operational governance that inventories AI tools, documents training data, and assigns accountability for outcomes, including bias monitoring and escalation when AI affects borrower eligibility, pricing, or disclosures.
Vendor risk has become a central exposure. Many technology contracts predate AI scrutiny and lack provisions on audit rights, explainability, and data controls, leaving lenders responsible when third-party models fail regulatory tests or transparency expectations.
Leading US mortgage lenders are using staged deployments, starting with lower-risk use cases such as document processing and fraud detection, while maintaining human oversight for high-impact decisions. Incremental rollouts generate performance and fairness evidence that regulators increasingly expect.
Regulatory pressure is rising as states advance AI rules and federal authorities signal the development of national standards. Even as boundaries are debated, lenders remain accountable, making early governance and disciplined scaling essential.
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Departures from Elon Musk’s AI startup xAI have reached a symbolic milestone, with two more co-founders announcing exits within days of each other. Yuhuai Tony Wu and Jimmy Ba both confirmed their decisions publicly, marking a turning point for the company’s leadership.
Losses now total six out of the original 12 founding members, signalling significant turnover in less than three years. Several prominent researchers had already moved on to competitors, launched new ventures, or stepped away for personal reasons.
Timing coincides with major developments, including SpaceX’s acquisition of xAI and preparations for a potential public listing. Financial opportunities and intense demand for AI expertise are encouraging senior talent to pursue independent projects or new roles.
Challenges surrounding the Grok chatbot, including technical issues and controversy over its harmful content, have added internal pressure. Growing competition from OpenAI and Anthropic means retaining skilled researchers will be vital to sustaining investor confidence and future growth.
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Officials in Russia have confirmed that no plans are underway to restrict access to Google, despite recent public debate about the possibility of a technical block. Anton Gorelkin, a senior lawmaker, said regulators clarified that such a step is not being considered.
Concerns centre on the impact a ban would have on devices running Android, which are used by a significant share of smartphone owners in the country.
A block on Google would disrupt essential digital services instead of encouraging the company to resolve ongoing legal disputes involving unpaid fines.
Gorelkin noted that court proceedings abroad are still in progress, meaning enforcement options remain open. He added that any future move to reduce reliance on Google services should follow a gradual pathway supported by domestic technological development rather than abrupt restrictions.
The comments follow earlier statements from another lawmaker, Andrey Svintsov, who acknowledged that blocking Google in Russia is technically feasible but unnecessary.
Officials now appear focused on creating conditions that would allow local digital platforms to grow without destabilising existing infrastructure.
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Lawmakers in the European Parliament remain divided over whether a direct ban on AI-driven ‘pornification’ should be added to the emerging digital omnibus.
Left-wing members push for an explicit prohibition, arguing that synthetic sexual imagery generated without consent has created a rapidly escalating form of online abuse. They say a strong legal measure is required instead of fragmented national responses.
Centre and liberal groups take a different position by promoting lighter requirements for industrial AI and seeking clarity on how any restrictions would interact with the AI Act.
They warn that an unrefined ban could spill over into general-purpose models and complicate enforcement across the European market. Their priority is a more predictable regulatory environment for companies developing high-volume AI systems.
Key figures across the political spectrum, including lawmakers such as Assita Kanko, Axel Voss and Brando Benifei, continue to debate how far the omnibus should go.
Some argue that safeguarding individuals from non-consensual sexual deepfakes must outweigh concerns about administrative burdens, while others insist that proportionality and technical feasibility need stronger assessment.
The lack of consensus leaves the proposal in a delicate phase as negotiations intensify. Lawmakers now face growing public scrutiny over how Europe will respond to the misuse of generative AI.
A clear stance from the Parliament is still pending, rather than an assured path toward agreement.
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A formal inquiry has been opened into how AI is used in the evaluation of the EU funding proposals, marking the first investigation of its kind at the institutional level.
European Ombudsman Teresa Anjinho initiated the probe following allegations that external experts relied on AI systems when assessing applications.
Concerns emerged after a Polish company failed to secure support from the European Innovation Council Accelerator programme after submitting its bid before the November 2023 deadline. The complainant alleged that third-party AI use compromised fairness and influenced the assessment outcome.
Requests have been made for clearer governance standards, including explicit disclosure when AI systems are used in proposal reviews. Fears also emerged that sensitive commercial data could be exposed through external AI platforms.
Despite no grounds to reopen the case, a systemic probe into AI transparency and safeguards was launched. Document inspections are scheduled through March, followed by institutional meetings in April to determine whether regulatory or procedural changes are warranted.
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