Rider Levett Bucknall teams up with Multiverse to launch the Data & AI Transformation Academy, empowering employees with cutting-edge skills in AI and data analytics to lead innovation in the construction industry. This initiative bridges the skills gap and drives digital transformation across key consultancy functions.

NVIDIA CEO Jensen Huang, awarded an honorary doctorate by HKUST, outlined a bold vision for AI and robotics. Highlighting the Greater Bay Area's unique integration of AI and electromechanical technologies, Huang predicts a future dominated by automobiles, drones, and humanoid robots. His forward-thinking insights position the region as a global robotics leader.

GPUs, hailed as the gold of AI, are driving unprecedented advancements in machine learning. NVIDIA's cutting-edge technology, from Tensor Cores to scalable supercomputers, powers everything from ChatGPT to industry-leading AI applications. Dive into the transformative role GPUs play in shaping AI's future.

Streem's collaboration with Google Cloud is set to revolutionize media monitoring with innovative AI tools. The 2025 AI Product Suite brings automated workflows, instant insights, and predictive analytics to PR and communications professionals, enhancing efficiency and decision-making. Find out how this partnership is reshaping the future of media intelligence.

The AI lifecycle is a comprehensive framework guiding AI projects from problem definition to operational success. By focusing on systematic phases — problem identification, data collection, training, evaluation, deployment, and monitoring — this approach ensures adaptable and impactful AI solutions. Explore how lifecycle tools enhance performance and empower dynamic applications.

UMass Boston's Applied Ethics Center stands at the forefront of ethical discourse, tackling complex issues in AI, technology, and society. With a commitment to research, teaching, and public engagement, the center is shaping the conversation on modern ethics and its impact on the future.

Amid an explosive growth of global data, AI emerges as a pivotal tool for enterprises seeking resilience and adaptability. This article explores how organizations can responsibly leverage generative AI to manage overwhelming data volumes, enhance decision-making, and build intelligent operations. Discover key strategies to harness AI effectively while safeguarding against the pitfalls of unregulated deployment.

Is superintelligence a decade away? As AI capabilities evolve rapidly, humanity faces both opportunities and risks. This article delves into the current state of AI, the ambitions for reaching superintelligence, and the critical balance required to ensure safe and beneficial development.

Dentsu’s 2025 Media Trends report reveals an “algorithmic era” where AI transforms media strategies. From dynamic personalization and retail media growth to impactful storytelling, discover how brands can leverage evolving trends for meaningful consumer engagement.

OpenAI's release of "Swarm" offers a glimpse into the future of multi-agent AI networks. While experimental, this framework has the potential to transform how businesses operate, driving automation to new levels while sparking important ethical discussions about AI governance and societal impact. Learn what this means for the future of AI collaboration and enterprise.

Physical AI is bridging the gap between the digital and physical worlds, transforming industries like manufacturing, healthcare, and urban living. As intelligent systems become more integrated into daily life, they offer unprecedented innovation while raising critical questions about ethics and the future of work.

Artificial Intelligence has long grappled with issues of truth and accuracy, often hindered by the very human thought processes that shape its development. However, a new wave of AI is emerging, one that adopts a more experimental methodology capable of propelling machine learning far beyond human capabilities. This shift marks a significant milestone in AI evolution, reminiscent of DeepMind’s groundbreaking achievements with AlphaGo.

In the midst of ongoing debates about artificial intelligence’s potential and pitfalls, OpenAI’s CEO, Sam Altman, has recently stirred the pot with his ambitious declaration of ushering in “The Intelligence Age”. Announcing on his personal website, Altman envisions a future dominated by superintelligent AI capable of monumental achievements like climate restoration, space colonization, and unraveling the mysteries of physics — all potentially just a few thousand days away.

Deep learning has surged to the forefront of scientific computing, powering innovations across healthcare, eCommerce, entertainment, and more. At its core, deep learning leverages artificial neural networks (ANNs) to perform complex computations on vast datasets, mirroring the human brain's structure and functionality. By learning from examples, these algorithms enable machines to recognize patterns, make predictions, and even generate creative content.

Q-learning is a way for machines to learn how to make better decisions over time. It’s like training a robot or an AI agent to act smartly by giving it feedback based on its actions. The key idea is that the AI learns from experience — every time it takes an action and receives a reward (or no reward), it remembers that experience and adjusts its future behaviour. Over time, it learns what actions lead to better outcomes.

OpenAI’s latest model, o1, represents a monumental shift in the way large language models (LLMs) approach problem-solving. Unlike traditional LLMs, o1 is trained using reinforcement learning, enabling it to "think" before providing an answer. This sophisticated training allows the model to develop a chain of thought, enhancing its ability to reason through complex problems in math, coding, and science. The key to this advancement lies in the reinforcement learning process, which enables o1 to progressively refine its thought process and self-correct. The model learns from its mistakes, breaks down difficult tasks into manageable steps, and adapts its approach when necessary. As a result, it performs significantly better than previous models on a wide range of challenging benchmarks.

In an era where repetitive tasks can be delegated to AI with just a simple command, the world is rapidly embracing Artificial Intelligence Generated Content (AIGC). Imagine asking an AI tool to generate entire reports, images, or even music, effortlessly — this future is no longer a distant dream but a reality. AIGC is transforming industries, offering a streamlined workflow for content creation across multiple sectors.

University students are often reminded that they might be preparing for careers that don’t yet exist. This notion has never been more accurate as the rapid advancement of artificial intelligence and emerging technologies continues to reshape the job market. Scientific futurist Dr. Catherine Ball, an honorary professor at the ANU School of Cybernetics, recently highlighted the impact of AI on future employment, noting that we are currently living through the fifth industrial revolution.

Reinforcement Learning (RL) is an advanced machine learning technique that empowers software to make decisions by learning from its experiences. Mimicking the trial-and-error process seen in human learning, RL systems are trained to pursue the most optimal outcomes by reinforcing successful actions and disregarding those that are less effective. This method allows AI to navigate complex environments with minimal human intervention, continuously refining its strategies to achieve set goals.

Mark Zuckerberg of Meta and Daniel Ek of Spotify have recently co-authored an opinion piece highlighting the transformative potential of artificial intelligence and advocating for Europe to fully embrace open-source AI. This piece underscores the importance of making AI technologies accessible and not just confined to a few major players in the tech industry.