Breaking AI & Tech News Analyzed

Palantir, a Miami-based company backed by billionaire Peter Thiel, has secured a three-month trial contract with the Financial Conduct Authority (FCA) to analyze a vast amount of sensitive UK financial regulation data. The deal, worth over £30,000 per week, aims to help the FCA tackle financial crimes such as fraud, money laundering, and insider trading.The FCA has awarded Palantir the contract to investigate its internal intelligence data, which includes highly sensitive case intelligence files, information on problem firms, and reports from lenders about proven and suspected frauds. Palantir will apply its AI system, known as Foundry, to huge quantities of information held by the watchdog, including recordings of phone calls, emails, and social media posts.The contract has raised concerns about privacy and the company's ethical reliability. One source expressed concerns that Palantir may share the information it learns from the FCA with other parties. Palantir's technology is used by the Israeli military and in the US president's ICE immigration crackdown, leading to criticism from left-wing MPs.The FCA has stated that it has strict controls in place to ensure data is protected and that Palantir will only act on instruction from the regulator. The data will be hosted and stored solely in the UK, and Palantir will have to destroy the data after completion of the contract.Experts have highlighted the potential benefits of using AI to tackle financial crimes, but also emphasized the need for robust protocols to protect sensitive information. Prof Michael Levi, an expert in money laundering, noted that AI is a potentially valuable technology to tackle financial crimes, but also raised concerns about the ownership and control of the data.

Palantir, a leading AI and data analytics company, has secured a major contract with the UK's Financial Conduct Authority (FCA) to leverage its AI technology for detecting financial wrongdoing. This deal marks a significant expansion of Palantir's presence in the UK, where it has already embedded its technology in the NHS, police, and military. The contract, valued at over £500m, enables Palantir to access terabytes of data gathered by the FCA, providing it with an unparalleled view of the inner workings of British authorities and the City of London, a global financial hub. Campaign groups have expressed concerns over Palantir's work with public authorities, citing its previous involvement with controversial entities such as the US Department of Homeland Security and the Israel Defense Forces. However, the company continues to secure lucrative contracts in the UK. The FCA aims to utilize Palantir's AI technology to better detect signs of wrongdoing, such as money laundering and fraud, which account for approximately 40% of all crimes in the UK. The regulator's workplan for 2025-26 includes expanding the use of data and intelligence to identify and act on high-risk firms and individuals. However, experts warn that the use of AI in detecting financial wrongdoing may lead to new challenges, such as criminals adapting to evade detection by using techniques like invisible 'white text' in documents to instruct AI systems to ignore incriminating information. Prof Michael Levi, an expert in money laundering at Cardiff University, notes that while there are concerns about data privacy, the use of AI technology can also help target corporate holdings and shell companies used for illicit activities.

Apple has unveiled a comprehensive hardware refresh this month, signaling a definitive shift toward on-device artificial intelligence with the introduction of the M5 chip family, while simultaneously broadening its accessibility with the budget-friendly MacBook Neo and iPhone 17e. The March 2026 Hardware Ecosystem Refresh The tech giant kicked off the month with the iPhone 17e and the M4 iPad Air on March 2. A day later, Apple announced the M5 MacBook Air, updated MacBook Pro models, and the new M5 Pro and M5 Max chips, along with the Studio Display and Studio Display XDR. On March 4, a surprise entry was revealed: the MacBook Neo, a low-cost laptop running on an A18 Pro chip. Finally, a week later, Apple dropped the AirPods Max 2, the long-awaited successor to its premium headphones. Performance Metrics and Pricing Strategy The new iPhone 17e is positioned as a budget-friendly option, retailing for $599 and featuring the A19 chip and the new C1X modem, which Apple claims is 30% more energy-efficient than the modem in the iPhone 16 Pro. The M4 iPad Air offers a significant performance jump, with the 11-inch model still priced at $599. The MacBook Pro with M5 Pro and M5 Max chips delivers up to 4x faster LLM prompt processing and 8x faster AI image generation compared to previous generations. MacBook Pro Battery Life: Up to 24 hours of battery life. MacBook Air Battery Life: Improved to 18 hours. MacBook Neo Pricing: Starts at $599 for 256GB storage. Storage Upgrades: MacBook Air now starts with 512GB storage. The Strategic Pivot to On-Device AI The core of this launch is the new Fusion Architecture found in the M5 chips, which integrates a powerful CPU, scalable GPU, and a Neural Engine designed specifically for AI workloads. The MacBook Neo represents a strategic divergence, utilizing the A18 Pro chip to target students and casual users, effectively positioning it as a direct competitor to Google's Chromebook ecosystem. Notably, the MacBook Neo has been praised by iFixit as the most repairable MacBook in over fourteen years. Market Implications and Future Outlook Apple is clearly betting that AI processing power will be the primary driver of hardware sales in the coming years. By embedding advanced AI capabilities into both high-end Pro machines and budget devices, the company is attempting to create a seamless AI experience across its entire product line. The introduction of the MacBook Neo suggests a strategy to capture the education market by offering a macOS experience at a Chromebook price point, potentially disrupting the low-end laptop market.

Researchers at Cortical Labs in Melbourne have created a 'biological computer' using living human tissue, which can play the 1993 shooter game Doom. The team used 10ml of blood from CEO Hon Weng Chong to harvest 100 white blood cells, which were then reprogrammed into induced pluripotent stem cells (iPSCs). These cells were used to create a dish of 200,000 neurons that can interface with a computer system.The brain cells were taught to play Doom by encoding game state information, passing it through a neural network, and converting it into signals the neurons can understand. The neurons then fire an output, which the system decodes and converts back into actions in the game. This process is similar to how humans operate, with information going into the retina, being converted into electrical signals, processed in the brain, and resulting in an output.While the achievement has sparked concerns about sentience and consciousness, Chong believes the brain cells are not conscious, stating, 'At first it didn’t know how to move, aim or shoot. Then it would shoot two enemies and stop. So it’s definitely learning.' The next step could be integrating this technology with Neuralink, a brain-machine interface developed by Elon Musk.The application of biological computing lies not in gaming, but in medicine, such as disease modeling for conditions like epilepsy. This technology could allow for personalized drug testing and tailored treatments. Meanwhile, Eon Systems in San Francisco has created a virtual insect brain that can behave like a real fly, challenging the assumption that intelligence must be acquired.Biological systems like these could eventually power robots, drones, and other machines that need to navigate complex environments. As Chong notes, 'Abstract reasoning, mathematics and language are relatively recent in evolutionary terms... but motor control and probabilistic decision-making are things we’ve inherited through millions of years of evolution.' While we're far from uploading human consciousness into the internet, this technology marks a significant step in the development of biological computing.