Latest news with #DaveLee
Mint
7 days ago
- Mint
Nilesh Jasani: Get set for a world of ever-evolving super-Einsteins
The early 2020s may well come to be remembered as the moment humanity discovered how to manufacture intelligence. At first, we welcomed chatbots—clever, conversational and occasionally cheeky, like digital butlers out of a Wodehouse novel. This was the Chatbot Era: amusing and useful, but still basic. Then came the current Agentic Era. No longer satisfied with talk, we sought action. Artificial intelligence (AI) has begun booking flights, editing selfies, navigating spreadsheets and doing several daily tasks. These early agents, while powerful, remain constrained—they are brilliant assistants, but still locked in their digital cribs. Also Read: Dave Lee: Apple must make peace with developers for AI success Yet, something far more transformative lies ahead. The third stage in this journey will see intelligence untethered from digital devices. This is when cognition escapes the screen and begins to permeate the physical world. Whether called embodied AI, robotics or the 'era of smart everything,' this phase will bring adaptive learning systems into everything from fork-lifts to furniture. Powered by action models, experience learning, multi-modal understanding and advanced hardware, machines will begin to learn from and reshape the world around them—physically, not just virtually. And even this would only be a warm-up. The fourth stage promises an intelligence explosion. We are rapidly approaching an era where the most complex and longstanding human challenges will be met with cognitive power vastly exceeding our own. Some AI models are already rivalling Olympiad-level students in mathematics. It is a matter of time before these systems surpass the most brilliant human minds in every discipline. This intelligence, endlessly scalable and tirelessly improving, will first prove its worth in the realm of health. Also Read: AI, identity and drama: Why everyone's turning into a character Smarter diagnostics as an early sign of Stage 4 success: While public fascination remains fixated on humanoid robots, self-driving cars and laundry-folding machines, the real transformation is already underway—in diagnostics. Here, AI has begun to outperform human experts in identifying disease from X-rays, cancer scans and medical imagery. These are not just marginal improvements. They are leaps in precision, speed and scalability. This diagnostic revolution is more than a healthcare upgrade. It signals AI's capacity to reason through complexity in ways that surpass even expert human cognition. If an algorithm can outperform trained radiologists, it suggests a broader capability to interpret, hypothesize and solve problems. These are cognitive feats previously limited to specialists. Now, machines are taking them on—and winning. Even if some of these breakthroughs still await peer-reviewed confirmation, the trend is unmistakable. Diagnostic models are showing that AI can attack complexity head-on, making decisions that would take humans days or weeks, within seconds. And diagnostics is only the beginning. Also Read: When AI gets a manager, you know the game has changed Drug discovery will be a bigger test: If diagnostics is about pattern recognition, drug discovery demands generative intelligence. It involves not only spotting problems, but imagining novel solutions, designing new molecules and validating hypotheses through layers of experimentation. Historically, biology has been structured around frameworks that made sense to humans—grouped proteins, labelled pathways, hierarchical taxonomies, etc. These simplifications helped us manage biochemical complexity but fell short of describing reality in full. Machines, however, are not bound by cognitive short-cuts. They operate across molecular spaces and mechanistic landscapes too vast for humans to hold in their mind. AI in drug discovery now proposes ideas, runs simulations and offers predictive insights across thousands of dimensions. Tools like Absci's zero-shot antibody generators can design viable drug candidates without needing examples. Recursion's phenomics platform screens tens of thousands of compound-cell combinations simultaneously. These capabilities hint at a new paradigm: one where machines don't just assist in discovery, they drive it. The real story isn't faster timelines or cheaper trials. It's the radical expansion of what's possible. AI is allowing science to ask more questions, explore more hypotheses and navigate a vastly larger solution space than ever before. Also Read: The agentic AI revolution isn't the future, it's already here This is only the beginning: What we see today is just the surface. Beneath it lies a revolution in how we interact with chemistry, biology and the material world. Synthetic biology is already leveraging AI to design gene circuits that function correctly on their first attempt. Antibody design is being reshaped by systems that require no training data. Whole-cell simulations are on the horizon. Predictive models now anticipate binding affinity, structural stability and biological impact without the need for physical experimentation. These shifts are not incremental; they're multiplicative. Each advance unlocks others. Taken together, they transform science from a linear process into something exponential. Beyond the spectacle: Today's headlines remain preoccupied with theatrical AI feats—machines that draft emails, pass exams, compose jingles or book your dinner reservation without being prompted. Entertaining, yes. Useful, perhaps. But these tasks belong to an ageing class of applications. The real story is elsewhere: We are not simply entering a world of better tools. We are entering a world with new minds—artificial ones that can reason in ways foreign to our own. These systems will not just support discovery; they will co-create it. Their thinking will be alien, powerful and deeply unfamiliar. And yet, increasingly, these tools will be indispensable. Also Read: The great AI reboot: Educators, techies and leaders all need to adapt fast At the same time, we are inevitably headed for complex terrain. Legal, ethical, moral, social and institutional questions—each deserving volumes of discussion—loom large. From accountability in autonomous systems to the governance of machine-generated knowledge, the implications are vast and underexplored. This article cannot do justice to those issues, but it can flag a simple truth: the genie is not going back in the bottle. What matters now is whether various communities—scientific, industrial, governmental and educational—start preparing for what lies ahead. Because Generative AI is not, and will not be, mostly about chatbots and digital assistants. Those tools dominate today's conversations, but they are unlikely to remain the defining story even a few quarters from now. We are on the cusp of something far greater. The sooner we recognize this, the better prepared we'll be for a future shaped not by chatterboxes or agents, but by minds we are only just beginning to comprehend. The author is a Singapore-based innovation investor for GenInnov Pte Ltd.
Yahoo
23-05-2025
- Business
- Yahoo
Can OpenAI Take on the iPhone With Jony Ive Deal?
Bloomberg Opinion columnist Dave Lee says OpenAI's $6.5 billion all-stock deal for Jony Ive's devices startup is a play to topple iPhone dominance. Lee speaks with Caroline Hyde and Ed Ludlow on "Bloomberg Technology."
Bloomberg
20-05-2025
- Business
- Bloomberg
Apple Prepares to Open AI Models to Third-Party App Developers
Good morning. Apple is said to open AI models to third-party developers. Humans can't keep up with developments in artificial intelligence. And Art Basel announces a fifth location. Listen to the day's top stories. Apple is betting that opening its AI models to third-party developers will revive its ailing App Store. The iPhone maker is working on a software development kit and related frameworks that will let outsiders build AI features based on the large language models that the company uses for Apple Intelligence, people familiar said. The new approach may be critically important because it's Apple's best chance to reset the negative energy around its AI work to date, Bloomberg Opinion 's Dave Lee writes.
Bloomberg
01-05-2025
- Business
- Bloomberg
What's Your iPhone Breaking Point?
Most customers will happily pay more for the latest iPhone if Apple increases prices to maintain margins due to Trump's tariff policies, explains Bloomberg Opinion columnist Dave Lee. (Source: Bloomberg)
Yahoo
30-03-2025
- Business
- Yahoo
CoreWeave Stock Debuts at $39 After Selling Shares for $40 A Piece
Shares of CoreWeave (CRWV) opened at $39 apiece during the company's debut on Nasdaq on Friday afternoon, just under its initial public offering which closed Thursday evening. The cloud computing firm had sold roughly 37.5 million shares at $40 each, raising about $1.5 billion for its initial public offering (IPO), making it the largest tech offering since 2021. It had, however, initially planned to file the offering at $47 to $55 a share at a much higher valuation than it ultimately saw. Nvidia, an early investor in the company, placed a $250 million order in the offering. Some experts speculated that the stock's debut wouldn't see the success it had hoped for. Bloomberg Opinion US technology columnist Dave Lee, for example, pointed out the company's large debt, reliance on just a few big customers and lack of diversity in revenue may be an issue. 'CoreWeave stands to be a bellwether for the AI industry as a whole — a must-watch stock as questions about return on investment grow ever louder,' Lee wrote in an op-ed on Friday. 'Even the slightest indication of shakiness in the belief of AI sends investors into a tailspin.' The current risk-off environment caused by the overall macro situation in the U.S., mainly due to recent tariffs imposed by U.S. President Donald Trump, which has caused a sell off in tech stocks, could also have weighed on CoreWeave's IPO.
