ANPD’s decision arose from concerns over Meta’s use of personal data to train its AI systems without users’ explicit consent. The agency warned of ‘serious and irreparable damage’ to the rights of data subjects and imposed a daily fine of 50,000 reais for non-compliance. Meta expressed disappointment, stating that the decision is a setback for innovation and AI development in Brazil.
The controversy in Brazil reflects broader global challenges for tech companies navigating stringent data privacy laws. In regions like the European Union, similar regulatory hurdles have forced Meta and other tech giants to pause their AI tool rollouts. Human Rights Watch highlighted risks associated with personal data in AI training, noting how personal photos, including those of Brazilian children, have been misused in image datasets, raising significant privacy and ethical concerns.
Meta’s response aligns with its recent actions in Europe, where it withheld its AI models due to regulatory uncertainties. This situation underscores the tension between advancing AI technologies and adhering to evolving data protection regulations.
Google France CEO Sébastien Missoffe highlighted Google’s infrastructure, data expertise, and long-term AI approach as key factors that will support CMA CGM’s growth. CEVA Logistics, CMA CGM’s logistics arm, will utilise Google’s AI-based management tools to enhance volume and demand forecasting, improving operational planning at its warehouses.
The partnership extends to CMA CGM’s media arm, which holds stakes in French private broadcaster M6 and recently acquired BFM TV. The media division aims to develop tools to help journalists synthesise and translate documents, generate media snippets for social networks, and digitise archives for research purposes. This collaboration underscores the growing trend of leveraging AI to address challenges across various industries, similar to the partnership between Airbus and Agrimetrics in agronomy.
Chinese companies have access to the much coveted Nvidia AI chips through their access to online cloud services owned by Google and Microsoft. The two American tech giants and other international companies rent to Chinese firms operating off-shore Nvidia-powered servers to power their data centres.
These and several other cloud service providers, including several AI startups, offer such services to companies across the globe. However, cloud service providers are based in more than just the US. Many operate out of Asia and Europe.
China’s access to these advanced AI semiconductors is noteworthy as the industry continues to benefit from an upswing, and the Biden administration continues to pressure local companies to ensure they uphold export regulations in place, targeting the ban on China.
The US Department of Commerce Secretary, Gina Raimondo, lamented the security risk China’s access to these chips poses to national security and promised to do more to prevent companies from skirting the legislation.
The EU antitrust regulators are investigating a deal between Google and Samsung, where Google’s chatbot, Gemini Nano, is embedded in Samsung’s Galaxy S24 smartphones. The European Commission wants to understand if this multi-year generative AI deal restricts rival chatbots from being installed on Samsung devices, raising concerns about potential anti-competitive practices.
Regulators have sent out a questionnaire to industry participants, asking if the pre-installation of Gemini Nano via the device or the cloud limits the number of other AI systems that can be pre-installed. They are also examining if this arrangement affects the interoperability between Gemini Nano and other pre-installed apps on Samsung smartphones.
The investigation aims to determine if competitors have faced challenges in making deals with device manufacturers for the pre-installation of their chatbots and the reasons behind any rejections. Feedback from industry participants is crucial in shaping the EU’s stance on the matter.
Respondents have until this week to submit their responses to the eight-page questionnaire, which will play a key role in assessing the impact of the Google-Samsung deal on market competition.
Britain’s new Labour government plans to investigate how to regulate the most powerful AI models but hasn’t proposed specific legislation yet. King Charles outlined Prime Minister Keir Starmer’s program for government, which includes over 35 new bills covering various areas, including cybersecurity.
The government aims to establish appropriate laws for developing advanced AI models. Former Prime Minister Rishi Sunak positioned the UK as a leader in AI safety, hosting a summit at Bletchley Park and launching the world’s first AI Safety Institute. However, Sunak’s administration avoided targeted AI regulation, preferring a sector-by-sector approach.
Nathan Benaich from Air Street Capital noted that AI labs are relieved by the government’s cautious approach. Nevertheless, some experts, like Gaia Marcus from the Ada Lovelace Institute, argue that the rapid development of AI tools necessitates urgent legislation.
The UK’s careful approach to AI regulation contrasts with the EU’s more proactive stance, potentially offering a competitive advantage. Starmer’s government remains committed to introducing new AI laws but is proceeding with caution.
The UJK Competition and Markets Authority (CMA) has requested further details from Amazon regarding its recent acquisition of leading executives and researchers from AI startup Adept. This move aligns with the CMA’s wider review of partnerships between major tech companies and AI startups, reflecting growing concerns about how these deals are structured.
Founded in 2022, Adept secured over £400 million in venture capital and was once valued at over £1 billion. Despite its promising beginnings, the company struggled to launch successful commercial products. The financial arrangements between Amazon and Adept remain unclear. The CMA is also investigating similar deals, such as Microsoft’s recruitment of leadership from another AI startup, Inflection AI.
The research involved 187 undergraduate students, each participating in around 12 four-minute speed dates. ChatGPT was found to perform on par with human judges in predicting the likelihood of contact exchange based solely on text transcripts. Although human judges with access to video footage were the most accurate, ChatGPT could interpret conversational nuances effectively from text alone.
Interestingly, the study revealed that positive emotions weren’t strong predictors of speed dating success. Both human judges and ChatGPT placed too much emphasis on these cues. Instead, references to money, health, and family were found to be stronger indicators of matching, although neither ChatGPT nor human judges considered them significant predictors.
Researchers concluded that LLMs could provide even more accurate judgments by analyzing longer initial interactions and incorporating additional metrics such as smiles, eye contact, and body language. The findings suggest that AI might soon play a key role in predicting romantic compatibility.
British regulators have launched a preliminary investigation into Microsoft’s recent hiring spree from AI startup Inflection AI and its entry into associated arrangements with Inflection AI, due to concerns that this could hinder competition in the burgeoning AI market. Mustafa Suleyman, Inflection AI’s co-founder and CEO, along with several top engineers and researchers, joined Microsoft earlier this year. Suleyman, a co-founder of the AI research lab DeepMind, is a prominent figure in the AI industry.
The UK’s Competition and Markets Authority (CMA) is scrutinising whether these hirings might lead to a significant reduction in competition within the UK’s AI sector, potentially breaching antitrust regulations. Microsoft, however, maintains that the recruitment of talent fosters competition and should not be regarded as a merger. The company has pledged to cooperate with the CMA’s inquiry.
The CMA has a deadline of 11 September to decide whether to approve the hirings or escalate the investigation. The authority has the power to reverse deals or impose conditions to address any competition concerns. This investigation highlights the growing regulatory scrutiny over how major tech companies are acquiring talent and technology from innovative AI startups.
Across the Atlantic, US senators have urged antitrust enforcers to investigate Amazon’s deal with AI startup Adept. The senators noted similarities to the Microsoft-Inflection case, emphasizing concerns over the potential elimination of major competitors in the AI market. These developments reflect a broader regulatory focus on maintaining competitive balance in the rapidly evolving AI industry.
The Federal Communications Commission (FCC) has unveiled a proposal to tighten regulations on AI-generated robocalls. Chairwoman Jessica Rosenworcel seeks public input on defining AI-generated calls, mandating disclosure by those using such technology, and supporting technologies that alert consumers to unlawful AI robocalls. The proposal aims to balance consumer protection with enabling beneficial uses of AI for people with disabilities.
State attorneys general would gain new powers to target businesses using AI-generated robocalls under the proposal, which the FCC will vote on in August 2024. In February 2024, the FCC classified calls with AI-generated voices as ‘artificial’ under the Telephone Consumer Protection Act (TCPA), making robocalls using voice cloning technology illegal. The agency has highlighted the risk of misinformation through AI calls imitating celebrities, politicians, and family members.
Rosenworcel’s initiative follows a series of FCC actions against AI-generated robocalls, including significant fines and mandates for service providers to combat illegal robocalls. Recently, the FCC fined a service provider and political operative $8 million for a campaign using voice-cloned calls of President Joe Biden to mislead voters before the New Hampshire primary.
Microsoft researchers have unveiled SpreadsheetLLM, a new method designed to help AI better understand and process spreadsheets. Combining encoding and compression techniques, SpreadsheetLLM aims to enhance AI performance in handling expansive grids and various cell formats, which are typically challenging for language models.
Their data revealed that using this method, the GPT-4 model saw a 27% improvement in spreadsheet table detection and a 26% boost in performance for in-context learning. Additionally, the method led to up to 96% cost reductions when using GPT-4 and GPT-3.5-turbo models.
Central to this innovation is Microsoft’s SheetCompressor, which includes modules that make spreadsheets more legible for AI, bypass empty cells, and help AI understand the meaning of numbers.
Future integration of SpreadsheetLLM into Microsoft Copilot for 365 could simplify data analysis, allowing users to upload entire spreadsheets and ask AI chatbot questions in plain language for data summaries or analysis. Although the method currently can’t handle spreadsheet formatting details, its implementation could significantly ease user data management tasks.
