Large Language Models (LLMs) are the new wizards of Wall Street, or so the story often goes. We’ve seen a flurry of research suggesting these AI powerhouses can digest vast amounts of financial data – news, company filings, market sentiment – and make savvy investment decisions. But a new study from
As we increasingly turn to Large Language Models (LLMs) like ChatGPT for everything from drafting emails to complex problem-solving, a thorny issue emerges: the privacy of the information we feed into them. When your prompts, containing potentially sensitive details, are sent to cloud-based LLMs, how can you be sure your
AI's Inner Monologue: More Chatter Than Clarity? We often wish we could peek inside the "mind" of an Artificial Intelligence, especially when it's a complex LLM tackling a tricky problem. One popular technique, known as "Chain-of-Thought" (CoT) prompting, encourages LLMs to "
If you ever had a brilliant idea for a LEGO masterpiece, perhaps scribbled on a napkin, you might have struggled translating that concept into a structurally sound, buildable model can be a surprisingly complex engineering challenge. Now, researchers from Carnegie Mellon University are bridging that gap with an ingenious AI
How does the intricate dance of neurons in our brain allow us to effortlessly chat, understand stories, or plan what we're going to say next? For decades, scientists have sought models to explain this remarkable feat. Traditionally, linguistic theories focused on symbolic rules, like grammar trees. But the
Large Language Models (LLMs) have fundamentally reshaped our interaction with information, demonstrating remarkable fluency and reasoning within the realm of text. Yet, the world isn't just text; it's a rich tapestry of images, sounds, and videos. Integrating these diverse modalities into AI systems typically involves complex
Artificial intelligence is rapidly moving from the lab into our lives. From self-driving cars navigating complex traffic to algorithms influencing healthcare decisions and even judicial sentencing, AI systems are increasingly granted autonomy. But with this growing power comes a profound question: how do we ensure these machines make decisions that
The relentless advance of artificial intelligence is no longer just about smarter algorithms or more capable chatbots. As systems grow increasingly complex, mimicking aspects of human cognition with startling fidelity, a profound and unsettling question emerges from the digital ether: could AI become conscious? And if so, how should we,
The quest to automate or augment scientific discovery using artificial intelligence isn't new. From early expert systems to modern deep learning, the dream persists: AI as a tireless collaborator, uncovering patterns and proposing hypotheses beyond human capacity. Recent advances in Large Language Models (LLMs) have reignited this possibility,