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Will artificial intelligence outsmart humankind? – Opinion

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OpenAI logo is seen near computer motherboard in this illustration taken Jan 8, 2024. [Photo/Agencies]

For a decade now, Sam Altman, the CEO and co-founder of Open-AI, one of the leading companies developing artificial intelligence, has been warning of the risks of AI.

There is, of course, a lot of hype around AI. And Altman has a lot to gain by talking up the capabilities of his company”s technology. But you don’t hear such existential warnings from leaders in other scientific fields that are changing our world.

Such worries go back a long time, to before the race to build AI even began. Today, some dismiss such existential worries as being too far off, and not worthy of much concern. After all, where are the self-driving cars that we’ve been long promised?

Andrew Ng, one of the most influential popularizers of AI, said at NVIDIA’s GPU Technology Conference in 2015: “I don’t work on preventing AI from turning evil for the same reason that I don’t work on the problem of overpopulation on the planet Mars.” Back in 2015, Ng had a point. AI was stuck in the laboratory, and a long way off impacting most people’s lives. It was still science fiction, not science fact. But that is no longer the case. AI is entering our lives. Even Tesla and SpaceX founder Elon Musk’s self-driving taxis recently turned up in Austin, Texas, and started offering rides to the public.

Indeed, what surprises me most about the development of AI today is the speed and scale of change. Significant resources are being poured into AI on a daily basis. We’ve never made such massive bets before on a single technology.

This unprecedented level of investment in AI is paying off. As a consequence, many people’s timelines for artificial general intelligence (AGI) when machines will match human intelligence are rapidly shrinking. Musk has predicted AGI by 2026. Dario Amodei, CEO of OpenAI competitor Anthropic, has said that “we’ll get there in 2026 or 2027”, while NVIDIA CEO Jensen Huang put the date as 2029.These predictions are all very near for such a portentous event.

Of course, there are also some dissenting scientific voices. Yann LeCun, Meta’s chief scientist, has argued that it will take several more decades for machines to exceed human intelligence. Another of my AI colleagues, Gary Marcus, said in 2024 that it will be “maybe 10 or 100 years from now”.

But whether you’re an optimist or a pessimist — indeed, I’m not even sure if it is optimistic or pessimistic to have a short AGI timeline — it seems scientifically plausible and therefore entirely reasonable to suppose AI will match and likely exceed human intelligence in the lifetime of our children. And we should probably entertain the idea that AGI might even happen in our own lifetime. That’s an exciting but scary thought.

We have, of course, had hundreds of years to get used to the idea that machines could be better than us. In the past, it was only our brawn that was bettered. Machines could do more work than any person. But soon it will be our brains that are overtaken.

It may come as a surprise to hear that the first world champion was beaten by a computer over four decades ago. In 1979, the world backgammon champion Luigi Villa was convincingly beaten 7-1 by Hans Berliner’s BKG 9.8 program. In a cruel twist, Villa had been world champion for just one day before this defeat.

More recently, in 1997, the reigning world chess champion Garry Kasparov was narrowly beaten by IBM’s Deep Blue computer. Discussing his loss, Kasparov described a future that awaits humankind. “I had played a lot of computers but had never experienced anything like this. I could feel — I could smell — a new kind of intelligence across the table. While I played through the rest of the game as best I could, I was lost; it played beautiful, flawless chess the rest of the way and won easily.”

But human chess hasn’t suffered from this machine dominance. Indeed, computer chess has improved the human game in several ways. Chess computers now provide professional coaching advice to human amateurs. And chess computers have opened up new avenues of play that we humans might never have considered. Our machine overlords have actually improved our game.

But there’s a more subtle reason why, as an AI researcher for 40 years, I don’t worry too much about AGI. It’s simply that intelligent people over-estimate the importance of intelligence. It’s not intelligence that’s the risk. It’s power.

AGI isn’t going to overthrow these existing power structures. It will have to exist within them. Also, AGI won’t have a free shot at goal. My AGI is going to be competing against your AGI. On the other hand, AGI can supercharge our economy, dramatically improve healthcare, and transform education.

The future is therefore bright. The future is AGI.

The author is a professor of AI and chief scientist of the AI Institute and UNSW Sydney, and author of five books on AI which have been published in a dozen countries including China. His most recent books are Faking It: Artificial Intelligence in a Human World and The Shortest History of AI: The Six Essential Ideas That Animate It.

The views don’t necessarily reflect those of China Daily.

If you have a specific expertise, or would like to share your thought about our stories, then send us your writings at opinion@chinadaily.com.cn, and comment@chinadaily.com.cn.



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3 Top Artificial Intelligence Stocks to Buy in September

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Artificial intelligence stocks have taken off recently, but these three laggards still look like strong long-term buys.

Many artificial intelligence (AI) stocks have taken off this year, rebounding strongly from early-year weakness. Still, there has been differentiation among AI beneficiaries. For instance, companies that have inked deals with current leader OpenAI, such as Oracle (NYSE: ORCL) and Broadcom (NASDAQ: AVGO), have soared. Meanwhile, those perceived to be on the outside of OpenAI and its immediate suppliers have lagged.

Yet, while investors have bid up recent outperformers to stratospheric valuations, we’re really just in the second inning of the artificial intelligence revolution. That means certain stocks that have sold off for short-term reasons this summer could be excellent pickups to ride the AI wave, as long as they find their place in this ongoing paradigm shift. In that light, the following three look like strong buys on weakness.

Super Micro Computer

Super Micro Computer (SMCI 2.50%) has been on a roller-coaster ride over the past year, crashing after its accounting firm quit last October, only to recover strongly after its new accountant gave the thumbs-up to its books in February.

However, Supermicro’s stock sold off after its recent earnings report, which underwhelmed on both the top and bottom lines. Supermicro said that its customers were a bit slow in making architectural decisions, while tariffs and write-downs on old inventory pressured gross margins.

But there could be better things on the horizon. Supermicro still grew revenue 47% in the fiscal year ending in June and forecasted at least 50% revenue growth in fiscal 2026. Supermicro management also said it expects to increase its large-scale data center customers from four to between six and eight in fiscal 2026. That could be a good thing for customer diversification.

Meanwhile, Supermicro is just ramping up its data center building block solutions (DCBBS), wherein the company will install not just server racks but also an entire data center in turnkey fashion, greatly speeding up deployment. Those efforts should help margins grow back toward the company’s old range of between 14% and 17%, up from 11.2% in the latest fiscal year, even if those margins don’t get all the way there in 2026.

In any case, Supermicro has sold off to a forward price-to-earnings (P/E) ratio of just 16 after the sell-off. Given the exceptionally strong longer-term guide for AI infrastructure growth provided by Oracle and others recently, that still seems like a low price to pay for a leading AI hardware player growing that quickly.

Applied Materials

Like Super Micro, Applied Materials (AMAT -1.21%) sold off after its own recent earnings release. While Applied beat revenue and earnings estimates for its third quarter, which ended July 27, management forecasted a slight revenue and earnings decline in the current quarter. Management attributed the downturn to “digestion” in China, as well as “uneven” ramps in leading-edge logic.

While that may seem worrisome, the reasons given seem reasonable. Applied’s results actually held up better than some peers during the post-pandemic downturn in semiconductors, so it may make sense that there is a little air pocket today.

And while the leading-edge logic fab buildout may be uneven, the rise of artificial intelligence should bolster growth over the medium term. Oracle forecasts robust AI data center growth through 2030, and all those data centers will need lots of chips.

Image source: Getty Images.

Applied is the most diverse semiconductor equipment supplier, so it should get a solid piece of that growing pie. Its equipment is concentrated in etch and deposition machines, which should see better-than-average growth over the next few years as chipmakers begin to implement new innovations such as gate-all-around transistors, backside power, and 3D architectures for both DRAM and logic chips, all of which are etch- and deposition-intensive.

Applied now trades at just 20 times earnings and 17 times next year’s estimates, which are below-market multiples. That seems absurdly cheap for a high-margin, cash-generating tech leader that should benefit from AI growth. Fortunately, Applied has rewarded shareholders with consistent share repurchases and a growing dividend, and that should continue going forward, even if the company has an off quarter here and there.

Intel

Finally, perhaps no tech company has been as maligned over the past few years as Intel (INTC -2.15%). After falling behind Taiwan Semiconductor Manufacturing (NYSE: TSM) in process technology and failing to anticipate the AI revolution, Intel spent the last four years on a spending spree in an attempt to catch up. That spending has added to Intel’s debt load and degraded its cash flow, while a lot of the fruits of that spending have not yet emerged.

Still, Intel recruited former board member and Cadence Design Systems (NASDAQ: CDNS) CEO Lip-Bu Tan as its new CEO, who is just a matter of months into his turnaround plan. Tan has unmatched experience and contacts within the semiconductor industry and seems like an ideal candidate to lead Intel at this stage.

Tan has made waves, cutting a massive amount of costs and restructuring the company. At a recent conference, CFO David Zinsner said Tan has already reduced management layers at the company from 11 to five. Meanwhile, Tan has also refreshed much of Intel’s leadership. In June, Tan promoted a new chief revenue officer and brought in several outside engineering leaders to lead Intel’s AI chip efforts.

At a recent industry conference, CFO David Zinsner stated that Tan would be laying out the company’s new AI roadmap soon. Then just last week, Tan named new heads of client and data center chip groups, completing his refreshment of Intel’s senior leadership. Given Tan’s wide experience as head of Cadence and his venture capital firm Walden Capital, which invests in AI start-ups, this new leadership is likely to strengthen Intel’s product portfolio.

Meanwhile, Intel’s first chip on its important 18A node will make its debut later this year, which management believes will give Intel equal or better technology than TSMC. And with the U.S. government recently taking a stake in the company and Tan having deep industry relationships, it seems likely Intel will land more external customers for its foundry, which will be another key to its success.

And yet, Intel trades just a touch above book value. But given that Tan is early in his transformation plan and the 18A node is just about to hit late this year, the stock is a great-looking risk-reward at these levels.



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Promising Artificial Intelligence Stocks To Watch Now – September 13th – MarketBeat

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Promising Artificial Intelligence Stocks To Watch Now – September 13th  MarketBeat



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This Artificial Intelligence (AI) Company Will Reshape Cloud Infrastructure by 2030

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  • The cloud infrastructure space got a jump start thanks to the surge in demand for AI.

  • Oracle Cloud Infrastructure (OCI) recently signed a flurry of deals that could take its business to the next level.

  • The company is on a path to become one of the world’s largest cloud providers.

  • 10 stocks we like better than Oracle ›

The advent of modern cloud computing is largely attributed to Amazon, which pioneered cloud infrastructure services with the introduction of Amazon Web Services (AWS) in 2002. The industry has evolved over time, but the basics remain the same: Providers offer on-demand, scalable computing, software, data storage, and networking capabilities to any business with an internet connection.

After a period of slower growth, the cloud infrastructure space got a jump start thanks to recent developments in the field of artificial intelligence (AI). However, the large language models that underpin the technology require a great deal of computational horsepower, which typically isn’t available outside a data center. As a result, the demand for cloud infrastructure services has skyrocketed in recent years, and it’s expected only to grow from here.

Recent developments suggest there could be a big shakeup coming to the cloud infrastructure space, led by technology stalwart Oracle (NYSE: ORCL).

Image source: Getty Images.

While the company is primarily known for its flagship Oracle Database, it offers customers a growing suite of enterprise software, integrated cloud applications, and cloud infrastructure services.

Oracle Cloud Infrastructure (OCI) has long trailed the Big Three cloud providers. To close out the calendar second quarter, AWS, Microsoft Azure, and Alphabet‘s Google Cloud controlled 30%, 20%, and 13% of the market, respectively, according to data compiled by Statista. Oracle ran a distant fifth with 3% of the market.

Yet, recent developments suggest a paradigm shift in the status quo. When Oracle released the results of its fiscal 2026 first quarter (ended Aug. 31), the headline numbers were largely business as usual. Total revenue grew 11% year over year to $14.9 billion, while its adjusted earnings per share (EPS) of $1.47 grew 6%.

However, investors were taken aback by the magnitude of Oracle’s backlog, as its remaining performance obligation (RPO) — or contractual obligations not yet included in revenue — surged 359% year over year to $455 billion. Perhaps more impressive is the $317 billion in contracts signed during the first quarter alone.

Oracle’s position as a trusted partner to enterprise made it “the go-to place for AI workloads,” according to CEO Safra Catz. If that wasn’t enough, she went on to say, “We expect to sign-up several additional multi-billion-dollar customers and RPO is likely to exceed half-a-trillion dollars.”



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