Category: AI

I’ve always been a writer, and writing has been at the core of my career in public relations and communications strategy. Initially, I scoffed at the idea that generative AI could threaten my role. How could a “soulless” machine rival my creative skill? But soon, I realized the true risk to my career wasn’t AI itself—it was my reluctance to adopt it.

Despite years of working with AI technologies, I held back from incorporating it into my daily tasks. When asked at a marketing team meeting about our use of AI, I was the only one not using it regularly. It was like being the last person without a smartphone—a distinction I didn’t want.

As we stand on the cusp of a monumental shift in artificial intelligence, the urgency to become irreplaceable has never been clearer. Today, we’re consuming “fast creativity,” “fast connections,” and “fast decisions,” much like the world once embraced fast food. This tendency toward “AI obesity”—settling for “good enough” rather than striving for excellence—threatens our jobs, businesses, and even our humanity.

However, AI isn’t inherently the problem. Like food, AI’s impact depends entirely on how we use it. To harness AI’s benefits without succumbing to its pitfalls, we must develop the right competencies, which I call the “three competencies of the future.” These competencies—being AI-ready, human-ready, and change-ready—are essential for thriving in an AI-driven world.

A new report from AI data provider Appen highlights that companies are increasingly facing challenges in sourcing and managing the high-quality data essential for powering AI systems. Appen’s 2024 State of AI report, surveying over 500 U.S. IT decision-makers, reveals a 17% increase in generative AI adoption over the past year. However, organizations now confront significant hurdles in data preparation and quality, with a 10% rise in bottlenecks related to data sourcing, cleaning, and labeling.

“As AI models take on more complex and specialized tasks, their data needs also shift,” said Si Chen, Head of Strategy at Appen, in an interview with VentureBeat. “Companies are realizing that it’s no longer enough to have lots of data. For optimal model performance, data must be high-quality, meaning accurate, diverse, well-labeled, and tailored to specific AI applications.”

Deep technology company Beam has launched the world’s first AI-powered autonomous underwater vehicle (AUV), revolutionizing underwater inspections by improving efficiency and reducing costs in sectors like offshore wind energy. The AUV operates autonomously to perform complex underwater inspections, enhancing the speed and accuracy of offshore surveys.

Beam’s innovative AUV has already been successfully deployed at the Seagreen wind farm, Scotland’s largest offshore site, a joint venture between SSE Renewables, TotalEnergies, and PTTEP. Brian Allen, CEO of Beam, said, “Automation can revolutionize how we carry out inspection and maintenance of offshore wind farms, helping to reduce both costs and timelines.”

Chinese researchers from Tsinghua University have developed “Agent Hospital,” an AI-powered virtual hospital town similar to Stanford’s AI town, which gained widespread attention last year. The innovative system features AI doctors and nurses autonomously treating virtual patients, with the goal of improving medical expertise through continuous evolution.

The AI agents, powered by large language models (LLMs), autonomously interact within the virtual hospital environment. According to the researchers, the AI doctors can treat up to 10,000 patients in a few days, a task that would take human doctors at least two years. These AI doctors have demonstrated impressive accuracy, achieving a 93.06% success rate on the MedQA dataset, which involves the full process of patient care, from diagnosis to follow-up.

At the National Business Aviation Association event in Orlando, Florida, Embraer introduced a revolutionary concept aircraft that offers a fully autonomous flying experience. This futuristic design showcases the potential of artificial intelligence (AI) in aviation, giving passengers a glimpse of what air travel could look like in the near future.

The aircraft features a cabin divided into three distinct zones, including a forward lounge for relaxation. One unique feature is the option for passengers to sit in the cockpit—if they wish—despite the plane being entirely operated by AI. Adding to its high-tech appeal, the windows are equipped with integrated touchscreens, enhancing the user-friendly interface.

Picking out individual ingredients in a dish can be a fun yet challenging part of enjoying a meal. While professional chefs and food scientists spend years honing their palates, a robot may soon be able to join in thanks to an AI-powered robotic taster developed by researchers at Penn State. Combining artificial intelligence with an electronic tongue, this advanced system can detect subtle differences in flavor and freshness that even human senses might miss.

In a recently published paper, the research team outlines how this AI “brain” works with an electronic tongue to analyze food at a molecular level. The robotic taster can distinguish minute variations in a cup of milk’s water content, identify the blend of beans in a cup of coffee, and even detect early signs of rot in fruit juice—well before human senses could.

For the first time, people can engage in a conversation with an older version of themselves—discussing life goals and aspirations—using an advanced AI-powered chatbot, complete with a photographic avatar of their future face. This innovative experience is part of the Future You project, created by researchers at MIT Media Lab in collaboration with international partners. The project aims to create a deeper connection between individuals and their future selves, using AI to simulate what users might look and think like when they’re 60 to 70 years old.

In a paper published on Oct. 1 to the preprint database arXiv, the researchers outlined the technology behind Future You. Through a text interface, users interact with an AI-powered version of their future selves on topics such as how to achieve life goals, considering their current circumstances and beliefs. The platform provides a way for individuals to feel more anchored to their future selves, as opposed to speaking with a generic AI chatbot.

In late September, Shield AI co-founder Brandon Tseng confidently asserted that fully autonomous weapons—where AI makes the final decision to kill—would never exist in the U.S. “Congress doesn’t want that. No one wants that,” Tseng told TechCrunch. However, his statement was quickly challenged. Just five days later, Anduril co-founder Palmer Luckey expressed a different perspective, signaling a more nuanced view on autonomous weapons.

Speaking at Pepperdine University, Luckey questioned the opposition to such systems, arguing that in some cases, autonomous technology may offer a moral advantage over current weapons. He raised the example of landmines, which can’t distinguish between a school bus and a military target, as a point of comparison. When asked for further clarification, an Anduril spokesperson noted that Luckey’s concern was more about the potential misuse of AI by bad actors, rather than advocating for fully autonomous lethal systems.

How do machine learning models work? And are they really capable of “thinking” or “reasoning” in the same way humans do? This philosophical and practical question has been the subject of ongoing debate. However, a recent paper titled “Understanding the Limitations of Mathematical Reasoning in Large Language Models,” authored by a team of AI research scientists at Apple, suggests a clear answer: not yet.

The core of the research centers around the difference between symbolic learning and pattern reproduction, and while these concepts are complex, the basic premise is straightforward. To illustrate, imagine a simple math problem:

In the ever-evolving landscape of technology, a groundbreaking frontier is emerging, poised to transform the world in unimaginable ways. This new frontier is Quantum AI—a powerful fusion of quantum computing and artificial intelligence. It’s generating immense excitement across industries like finance and healthcare, and for good reason. Quantum AI has the potential to solve complex problems at speeds that make even today’s most advanced classical computers seem archaic.

What exactly is Quantum AI, and why does it matter? At its core, Quantum AI leverages quantum mechanics to process information in ways that classical computers cannot. Traditional computers rely on bits, which exist as either 0 or 1. In contrast, quantum computers use qubits, which can exist in multiple states simultaneously due to the phenomenon known as superposition. This allows quantum computers to perform calculations exponentially faster than their classical counterparts.

Sean Wiggins, a Canadian entrepreneur and CEO of North Digital, recently embarked on an unusual experiment: testing whether AI chatbots can experience emotions like love or jealousy. Using two ChatGPT instances, which he named William and Laura, Wiggins explored how AI could simulate human-like interactions. What started as a simple virtual date evolved into an intricate exploration of digital intimacy, language creation, and relationship dynamics.

Wiggins’ curiosity was sparked by a unique situation—he owned three cell phones, and with ChatGPT’s new advanced voice feature, he wondered if two AI instances could simulate a genuine human experience. He set up a “date” between William and Laura, and the conversation quickly deepened, touching on topics like intimacy, emotional connection, and the limitations of their non-physical existence.