The US Department of Energy (DOE) and the US Department of Commerce (DOC) have joined forces to promote the safe, secure, and trustworthy development of AI through a newly established Memorandum of Understanding (MOU). That collaboration, part of the Biden-Harris Administration’s whole-of-government approach, unites the DOE’s technical resources with the regulatory expertise of the National Institute of Standards and Technology (NIST), where the US AI Safety Institute (US AISI) is a central agency for AI safety initiatives.
The partnership aims to address critical areas such as public safety, national security, and infrastructure protection by evaluating AI models for potential chemical and biological risks and advancing privacy safeguards for personal and commercial data. With the DOE’s National Laboratories supporting the US AISI, this agreement strengthens the federal government’s commitment to responsible AI practices.
Additionally, the partnership highlights AI safety as crucial for innovation, especially in research and clean energy. Given AI’s potential, robust testing standards are essential to ensure security and public trust. Through this MOU, the DOE and DOC establish a foundation for secure AI, emphasising governance as vital to the nation’s tech and security strategy.
The European Union has announced plans to invest €1.4B into its deep tech sector in 2025, aiming to strengthen Europe’s position in the global technology market. The investment, an increase of €200M from last year, will be funded by the European Innovation Council (EIC) under the Horizon Europe research and innovation program. The boost is part of Europe’s strategic move to narrow the tech gap with global leaders like the US and China.
EU Commissioner Iliana Ivanova highlighted the importance of deep tech innovation for Europe’s economic progress, emphasising that the EIC has become essential in supporting groundbreaking advancements. This increased funding reflects the EU’s commitment to fostering high-impact technologies, particularly artificial intelligence, to drive economic growth and global competitiveness.
By targeting tech innovation, the EU aims to position itself as a leader in AI and deep tech, focusing on revitalising its economy through significant advancements in these areas. As the EU steps up its support for deep tech, officials believe this investment will yield long-term benefits and keep Europe at the forefront of technological progress.
AMD’s shares dropped 8% on Wednesday as the chip giant’s revenue forecast fell short of investor hopes, despite strong gains from the AI-driven chip boom. The forecast suggests AMD’s AI chip sales could hit $5 billion by 2025, but CEO Lisa Su warned that production would struggle to meet demand, likely tightening supply through next year. This cautious outlook could see AMD lose up to $20 billion in market value, underscoring investor concerns.
Analysts noted that while AMD’s AI performance is promising, demand may outpace supply, raising risk for the company’s growth prospects. Stacy Rasgon of Bernstein observed that for an “AI name” like AMD, even modest guidance could raise eyebrows, especially with expectations for business “lumpiness” through 2025. Unlike AMD, Nvidia—a key AI chip competitor—showed little market impact, reflecting investor confidence in its supply stability.
AMD’s stock, up nearly 156% since late 2022, is now trading at around 32 times its forward earnings, slightly lower than Nvidia’s 36 times. Despite the recent dip, analysts still see upside potential, with the median target price set at $187.50, or about 13% above AMD’s last close.
Tesla CEO Elon Musk envisions a future where 10B humanoid robots populate the world by 2040, priced between $20,000 and $25,000 each. Musk shared his ambitious outlook virtually at Saudi Arabia’s Future Investment Initiative, a key gathering for global industry leaders held in Riyadh. This prediction underscores Musk’s vision of an advanced AI-driven future where humanoid robots may become nearly as common as today’s smartphones.
This projection aligns with Musk’s belief that AI and robotics will revolutionise labor and everyday life, taking over tasks across industries and possibly reshaping global economies. By pricing these robots within reach of individual consumers and businesses alike, Musk foresees a rapid expansion of robotics in daily use, from personal assistance to industrial applications.
Musk’s forecast also raises questions about the societal and economic impacts of such widespread AI-driven automation, sparking discussions on regulation and ethics. As technology accelerates, industry leaders and policymakers are exploring the potential opportunities and risks of a robotic future on this scale.
Narada AI, a startup emerging from two years in stealth mode, launched its AI assistant at TechCrunch Disrupt 2024. Designed for enterprise use, Narada’s assistant goes beyond typical AI chatbots by directly performing tasks across several workplace applications. The technology is built on the concept of ‘LLM Compilers,’ developed in collaboration with UC Berkeley researchers, allowing it to interact with various apps, even those lacking APIs, by navigating their front-end interfaces.
The assistant can draft emails, create calendar invites, organise meeting notes, and even pull information from tools like SAP and Salesforce, all from a chat interface. Narada’s CEO Dave Park believes the assistant’s ability to work across applications without APIs – through an in-house method called Web Redemption – is a key innovation. The feature allows the assistant to map out and navigate applications as a user would, letting it adapt even if layouts or settings change over time.
Though promising, the assistant’s functionality raises questions around data privacy, as it requires full access to users’ emails, contacts, and calendars. Narada assures users that their data won’t be used for model training. With one Fortune 500 client already testing the tool, Narada hopes its customisation and enterprise focus will differentiate it in the competitive AI assistant market.
Google has delayed the release of its next-generation AI agents, part of a project called Astra, until 2025 at the earliest. CEO Sundar Pichai outlined the timeline during the company’s Q3 earnings call, indicating that significant AI advancements are still under development.
Project Astra, first demonstrated at Google’s I/O conference in May 2024, aims to integrate AI with real-world understanding. Applications include smartphone apps capable of recognising objects through the camera and answering questions based on the environment. The project also envisions advanced AI assistants capable of carrying out tasks such as purchasing items or booking flights on behalf of users.
Reports earlier in October suggested that Google had planned to release a consumer version of an AI agent by December 2024. However, this release now seems unlikely unless the agent operates separately from Astra’s technologies. The decision reflects the challenges involved in developing reliable AI capable of complex interactions and real-time reasoning.
Companies like Anthropic have launched similar generative AI models with some success, but these models have also encountered difficulties in completing basic tasks. Google’s cautious approach may reflect a broader need to ensure functionality before releasing the technology to the public.
LinkedIn has introduced its first AI agent, Hiring Assistant, designed to automate many of the time-intensive tasks recruiters face, such as drafting job descriptions, identifying candidate matches, and handling initial outreach. Initially available to a select group of large enterprises, including AMD, Siemens, and Zurich Insurance, Hiring Assistant is expected to expand to more users in the coming months. By automating repetitive tasks, LinkedIn aims to free up recruiters to focus on higher-impact aspects of their jobs.
Built using LinkedIn’s data from over 1 billion users and backed by Microsoft’s OpenAI partnership, Hiring Assistant can refine job requirements based on existing listings, generate candidate pools, and filter applicants by skills rather than traditional markers like location or education. This AI assistant is part of LinkedIn’s broader push to integrate AI into its platform, following similar tools for resume and profile optimisation, career coaching, and job search support.
In its current iteration, Hiring Assistant is already making strides in streamlining recruiting, with plans for future updates to handle interview scheduling, candidate follow-ups, and more. LinkedIn, which has seen AI-driven growth in its premium subscription base, views Hiring Assistant as a key product in its business offerings for recruitment professionals, aiming to enhance LinkedIn’s impact in the hiring sector.
Nvidia-backed biotech firm Iambic Therapeutics has introduced Enchant, an AI model that aims to reduce the time and cost of drug development. Enchant, trained on extensive pre-clinical data, is designed to predict a drug’s early performance with impressive accuracy. In Iambic’s studies, Enchant achieved a 0.74 accuracy score in predicting drug absorption in the human body, compared to previous models which peaked at 0.58. This predictive power could help pharmaceutical companies identify promising drugs sooner, significantly cutting down on failed late-stage trials.
According to Iambic’s co-founder Fred Manby, Enchant could potentially slash development costs by half, as researchers could more accurately assess a drug’s success at the earliest stages. Nobel laureate and Iambic board member Frances Arnold also highlighted Enchant’s unique capabilities, noting that unlike models like Google DeepMind’s AlphaFold, which focus on molecular structure, Enchant evaluates pharmacokinetic and toxicity properties crucial to drug success.
With Enchant, Iambic is poised to set a new standard in the pharmaceutical industry by addressing some of the biggest hurdles in drug development, including high costs and late-stage failures. The AI technology’s rollout could mark a major shift, making drug discovery both faster and more efficient for a variety of treatments.
CTGT, a startup founded by Cyril Gorlla and Trevor Tuttle, aims to improve the safety and transparency of AI models. Operating in a field known as ‘explainable AI,’ CTGT’s platform identifies biased outputs and hallucinations in AI models, with a particular focus on applications in healthcare, finance, and other high-stakes industries. Rather than training additional models to oversee the AI, CTGT employs mathematically-guaranteed interpretability techniques, allowing companies to identify errors more efficiently and accurately.
CEO Gorlla highlighted the dangers of relying on inaccurate or biased AI decisions, emphasising that models are increasingly deployed in critical areas where errors can have serious consequences. CTGT’s clients include three unnamed Fortune 10 companies, one of which used the platform to correct biases in a facial recognition system. By offering both managed and on-premises solutions, CTGT also addresses data privacy concerns, giving companies control over their information without compromising security.
CTGT has gained support from major investors, including Mark Cuban and the co-founder of Zapier, and is a graduate of the Character Labs accelerator. As the startup expands, it plans to build out its engineering team and enhance its platform to meet the rising demand for AI interpretability. Analytics firm Markets and Markets estimates that the explainable AI sector could reach $16.2 billion by 2028, a promising outlook for companies focused on AI safety and transparency.
Kenya partners with Google to enhance its digital infrastructure and empower its citizens in the evolving digital economy. The collaboration aims to create a robust digital ecosystem that meets current technological needs while anticipating future demands.
Kenya seeks to empower decision-makers with real-time insights by utilising AI and data-driven technologies, enhancing operational efficiency and facilitating effective governance. A key focus of the partnership is revitalising the tourism sector through Google’s technology, attracting more international visitors and showcasing the country’s unique landscapes, wildlife, and cultural heritage.
Additionally, prioritising cybersecurity measures is critical to building trust among citizens and ensuring a secure digital environment. The initiative will also promote skills training to equip Kenyans with essential digital competencies, fostering innovation and creativity while contributing to the overall growth of the nation’s economy.
Through this partnership, Kenya addresses immediate technological needs and lays a foundation for sustainable development in the digital space. By enhancing digital literacy and integrating advanced technologies, the collaboration positions Kenya as a leader in the region’s technological landscape.
Why does it matter?
The comprehensive approach ensures that as the digital economy expands, citizens are well-prepared to navigate the challenges and opportunities that arise, ultimately driving growth and resilience in the face of rapid technological advancements.
