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Tech giants join forces to promote global standards for data provenance and AI transparency

OASIS Open, a global open-source and standards organisation, and the Data & Trust Alliance, a consortium focused on responsible data and AI practices, have announced the formation of the OASIS Data Provenance Standards Technical Committee (DPS TC).

The committee will build upon version 1.0.0 of the Data Provenance Standards developed by the Data & Trust Alliance’s cross-industry Working Group, expanding industry participation to establish formal technical standards for data transparency, accountability, and trust. Founding sponsors include Cisco, IBM, Intel, Microsoft, and Red Hat.

As AI adoption accelerates, organisations face increasing challenges in verifying data sources, ensuring compliance, and maintaining data integrity. The DPS TC aims to create a standardised metadata framework that tracks data lineage, transformations, and compliance across various platforms. This initiative will help organisations improve governance practices, mitigate risks related to data privacy and intellectual property, and enhance transparency in AI-driven applications.

The committee’s work will focus on:

  • Standardised data lineage tracking: Establishing clear and consistent methods for documenting data origins and transformations.
  • Compliance and risk management: Supporting organisations in meeting regulatory and ethical standards for data use.
  • Interoperability across platforms: Ensuring metadata models can be applied consistently across different databases, tables, and data pipelines.
  • Transparency for data users: Providing businesses and individuals with visibility into how data is sourced and managed.

IBM has already tested an early version of the standards, integrating them into its governance framework. According to Christina Montgomery, Chief Privacy and Trust Officer at IBM, this resulted in measurable improvements in data diligence and management processes.

The DPS TC will hold its first meeting on 8 April 2025, with participation open to organisations, industry leaders, and experts through OASIS membership. The committee aims to refine existing standards and develop implementation tools, with a goal of introducing broadly applicable metadata quality metrics within the next 12 to 18 months.

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Spain approves bill to regulate AI-generated content

Spain’s government has approved a bill imposing heavy fines on companies that fail to label AI-generated content, aiming to combat the spread of deepfakes.

The legislation, which aligns with the European Union’s AI Act, classifies non-compliance as a serious offence, with penalties reaching up to €35 million or 7% of a company’s global revenue.

Digital Transformation Minister Oscar Lopez stressed that AI can be a force for good but also a tool for misinformation and threats to democracy.

The bill also bans manipulative AI techniques, such as subliminal messaging targeting vulnerable groups, and restricts the use of AI-driven biometric profiling, except in cases of national security.

Spain is one of the first EU nations to implement these strict AI regulations, going beyond the looser US approach, which relies on voluntary compliance.

A newly established AI supervisory agency, AESIA, will oversee enforcement, alongside sector-specific regulators handling privacy, financial markets, and law enforcement concerns.

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OpenAI launches responses API to boost AI agents

OpenAI has unveiled new tools for developers to build advanced AI agents, stepping up its game amid rising competition from Chinese startups.

The latest offering, called the Responses API, allows developers to create AI systems that execute complex tasks independently. This new tool replaces the Assistants API, which will be phased out by mid-2026.

The launch comes as Chinese startups make rapid advances in AI, with some claiming their models rival or surpass those of leading US firms at a lower cost.

One such company, Monica, recently introduced its autonomous AI agent, Manus, which it says outperforms OpenAI’s DeepResearch agent.

Monica’s rise follows growing recognition of Chinese AI innovations, including DeepSeek, which has impressed Silicon Valley executives.

On Tuesday, Monica announced a partnership with the team behind Alibaba’s Qwen AI models, further intensifying the global AI race.

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ServiceNow expands AI capabilities with $2.9B acquisition

ServiceNow has struck a significant deal, acquiring AI firm Moveworks for $2.85 billion in cash and stock, marking its largest-ever acquisition. This move comes as companies are increasingly investing in generative AI to streamline operations. ServiceNow, which is based in Santa Clara, California, US, plans to integrate Moveworks’ AI technology into its own platform, further enhancing its IT operations offerings.

Moveworks, known for its AI solutions that help resolve employee issues through chat, has a strong customer base, including companies like Broadcom, Palo Alto Networks, and Pinterest. The deal will bring more than 500 employees from Moveworks into ServiceNow, with no layoffs anticipated.

Despite the deal’s size, ServiceNow does not expect regulatory challenges to hinder the transaction, which is expected to close in the second half of 2025. Following the announcement, ServiceNow’s shares saw a 7% dip. Moveworks had previously raised $315 million, reaching a valuation of $2.1 billion before this acquisition.

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Gmail adds ‘add to calendar’ button with Gemini AI

Google has introduced a new feature in Gmail, powered by its Gemini AI, allowing users to seamlessly add events to their Google Calendar.

Starting this week, Gmail users can click an ‘Add to calendar’ button when Gemini detects calendar-related content in an email, simplifying the process of scheduling events directly from emails.

Currently available in English and only for web users, the feature is part of Google Workspace’s offerings, targeting Business and Enterprise tier users, along with customers subscribed to premium Gemini plans.

Notably, it does not include the addition of other guests to the event or apply to certain pre-extracted events like restaurant or flight reservations.

This addition follows other Gemini-powered updates, such as features for email summarization and enhanced search capabilities, and aims to streamline workflow for users.

As Google continues expanding AI-powered tools within Gmail, this new feature further demonstrates the integration of advanced AI into productivity apps.

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Chinese investors turn to AI for stock market edge

Chinese retail investors are rapidly embracing AI tools like DeepSeek to navigate the stock market, marking a striking shift from last year’s government crackdown on computer-driven quantitative trading.

Online courses and packed training rooms reflect a growing eagerness among small-time traders to use AI-powered models, with many seeing them as essential in the digital age.

DeepSeek, developed by a hedge fund in Hangzhou, has not only boosted Chinese stocks but also reshaped perceptions of the country’s $700 billion hedge fund industry.

Despite the initial backlash against quant funds, which were previously blamed for market volatility, investors are now paying thousands of yuan to attend AI trading seminars.

Social media is flooded with courses teaching traders how to use DeepSeek to analyse companies, pick stocks, and even code their own trading strategies.

While major US funds like BlackRock and Renaissance Technologies have long used AI for investments, DeepSeek’s open-source model makes these tools accessible to China’s smaller asset managers and individual traders.

Financial institutions are also adapting to the AI-driven shift. Brokers are rushing to integrate AI models into their platforms, with industry leaders predicting a complete transformation in how Chinese investors make decisions.

Many now seek trading advice from DeepSeek instead of human wealth managers, reflecting a deep trust in the technology. However, experts warn that AI models still have limitations and could create market risks, especially if large numbers of traders act on the same signals.

While some remain cautious about AI’s role in investing, DeepSeek has undeniably changed public attitudes towards quant fund managers.

Many now view them as contributors to market efficiency rather than as culprits behind retail losses. As China’s stock market continues to evolve, AI looks set to play an increasingly dominant role in shaping investor behaviour.

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Meta has developed an AI chip to cut reliance on Nvidia, Reuters reports

Meta, the owner of Facebook, Instagram, and WhatsApp, is testing its first in-house chip designed for training AI systems, sources told Reuters.

The social media giant has started a limited rollout of the chip, planning to scale up production if testing delivers positive results. The move represents a crucial step in Meta’s strategy to lessen dependence on external suppliers like Nvidia and lower substantial infrastructure costs.

The company has projected expenses between $114 billion and $119 billion for 2025, with up to $65 billion dedicated to AI infrastructure.

The chip, part of Meta’s Meta Training and Inference Accelerator (MTIA) series, is a dedicated AI accelerator, meaning it is specifically designed for AI tasks rather than general processing. This could make it more power-efficient than traditional GPUs.

Meta is collaborating with Taiwan-based chip manufacturer TSMC to produce the new hardware. The test phase follows Meta’s first ‘tape-out’ of the chip, a crucial milestone in silicon development where an initial design is sent to a chip factory.

However, this process is costly and time-consuming, with no guarantee of success, and any failure would require repeating the tape-out step.

Meta has previously faced setbacks in its custom chip development, including scrapping an earlier version of an inference chip after poor test results. However, the company has since used another MTIA chip for AI-powered recommendations on Facebook and Instagram.

The new training chip aims to first enhance recommendation systems before expanding to generative AI applications like the chatbot Meta AI.

Meta executives hope to implement their own chips for AI training by 2026, although the company continues to be one of Nvidia’s biggest customers, investing heavily in GPUs for its AI operations.

The development comes as AI researchers increasingly question whether scaling up large language models by adding more computing power will continue to drive progress. The recent emergence of more efficient AI models, such as those from Chinese startup DeepSeek, has intensified these debates.

While Nvidia remains a dominant force in AI hardware, fluctuating investor confidence and broader market concerns have caused turbulence in the company’s stock value.

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Google revises AI team’s mission statement, removing equity focus

Google has quietly updated the webpage for its Responsible AI and Human-Centred Technology team, removing references to diversity and equity

Terms such as ‘marginalised communities’ and ‘underrepresented groups’ have been replaced with more neutral language. The changes were first spotted by watchdog group The Midas Project, which previously reported similar edits to Google’s Startups Founders Fund page.

The company’s move comes amid a broader rollback of diversity, equity, and inclusion (DEI) initiatives across the tech industry. Google announced in February that it would end its diversity hiring targets and reassess its DEI programmes.

Other companies, including Amazon and Meta, have also scaled back diversity policies in response to legal and political pressures from the Trump administration, which has criticised such initiatives.

Federal contracts could be influencing these decisions, as many of the affected companies, including Google, work closely with United States agencies.

While some firms, such as OpenAI, have removed diversity language from hiring pages, Apple recently rejected a shareholder proposal to eliminate its DEI programmes. The changes suggest a shifting landscape for corporate diversity efforts in the US tech sector.

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US drops AI investment proposal against Google

The US Department of Justice (DOJ) has decided to drop its earlier proposal to force Alphabet, Google’s parent company, to sell its investments in AI companies, including its stake in Anthropic, a rival to OpenAI.

The proposal was originally included in a wider initiative to boost competition in the online search market. The DOJ now argues that restricting Google’s AI investments might lead to unintended consequences in the rapidly changing AI sector.

While this move represents a shift in the government’s approach, the DOJ and 38 state attorneys general are continuing their antitrust case against Google. They argue that Google holds an illegal monopoly in the search market and is distorting competition.

The government’s case includes demands for Google to divest its Chrome browser and implement other measures to foster competition.

Google has strongly opposed these efforts, stating that they would harm consumers, the economy, and national security. The company is also planning to appeal the proposals.

As part of the ongoing scrutiny, the DOJ’s latest proposal mandates that Google notify the government of any future investments in generative AI, a move intended to curb further concentration of power in the sector.

This case is part of a broader wave of antitrust scrutiny facing major tech companies like Google, Apple, and Meta, as US regulators seek to rein in the market dominance of Big Tech.

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Authors challenge Meta’s use of their books in AI training

A lawsuit filed by authors Richard Kadrey, Sarah Silverman, and Ta-Nehisi Coates against Meta has taken a significant step forward as a federal judge has ruled that the case will continue.

The authors allege that Meta used their books to train its Llama AI models without consent, violating their intellectual property rights.

They further claim that Meta intentionally removed copyright management information (CMI) from the works to conceal the alleged infringement.

Meta, however, defends its actions, arguing that the training of AI models qualifies as fair use and that the authors lack standing to sue.

Despite this, the judge allowed the lawsuit to move ahead, acknowledging that the authors’ claims suggest concrete injury, specifically regarding the removal of CMI to hide the use of copyrighted works.

While the lawsuit touches on several legal points, the judge dismissed claims related to the California Comprehensive Computer Data Access and Fraud Act, stating that there was no evidence of Meta accessing the authors’ computers or servers.

Meta’s defence team has continued to assert that the AI training practices were legally sound, though the ongoing case will likely provide more insight into the company’s stance on copyright.

The ruling adds to the growing list of copyright-related lawsuits involving AI models, including one filed by The New York Times against OpenAI. As the debate around AI and intellectual property rights intensifies, this case could set important precedents.

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