Samsung Elec Starts 3-Nanometer Chip Production to Lure New Foundry Customers

This undated handout photo provided by Samsung Electronics on June 30, 2022 shows leaders of Samsung Foundry Business and Semiconductor R&D Center posing to celebrate the company's first production of 3-nanometer process chips at its semiconductor facility of Samsung Electronics Hwaseong Campus in Hwaseong. (Samsung Electronics / AFP)
This undated handout photo provided by Samsung Electronics on June 30, 2022 shows leaders of Samsung Foundry Business and Semiconductor R&D Center posing to celebrate the company's first production of 3-nanometer process chips at its semiconductor facility of Samsung Electronics Hwaseong Campus in Hwaseong. (Samsung Electronics / AFP)
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Samsung Elec Starts 3-Nanometer Chip Production to Lure New Foundry Customers

This undated handout photo provided by Samsung Electronics on June 30, 2022 shows leaders of Samsung Foundry Business and Semiconductor R&D Center posing to celebrate the company's first production of 3-nanometer process chips at its semiconductor facility of Samsung Electronics Hwaseong Campus in Hwaseong. (Samsung Electronics / AFP)
This undated handout photo provided by Samsung Electronics on June 30, 2022 shows leaders of Samsung Foundry Business and Semiconductor R&D Center posing to celebrate the company's first production of 3-nanometer process chips at its semiconductor facility of Samsung Electronics Hwaseong Campus in Hwaseong. (Samsung Electronics / AFP)

Samsung Electronics Co Ltd said on Thursday it has begun mass producing chips with advanced 3-nanometer technology, the first to do so globally, as it seeks new clients to catch far bigger rival TSMC in contract chip manufacturing.

Compared with conventional 5-nanometer chips, the newly developed first-gen 3-nanometer process can reduce power consumption by up to 45%, improve performance by 23%, and reduce area by 16%, Samsung said in a statement.

The South Korean firm did not name clients for its latest foundry technology, which supplies made-to-order chips like mobile processors and high-performance computing chips, and analysts said Samsung itself and Chinese companies are expected to be among the initial customers.

Taiwan Semiconductor Manufacturing Co (TSMC) is the world's most advanced foundry chipmaker and controls about 54% of the global market for contract production of chips, used by firms such as Apple and Qualcomm which don't have their own semiconductor facilities.

Samsung, a distant second with a 16.3% market share, according to data provider TrendForce, announced a 171 trillion won ($132 billion) investment plan last year to overtake TSMC as the world's top logic chipmaker by 2030.

"We will continue active innovation in competitive technology development," said Siyoung Choi, Head of Foundry Business at Samsung.

Samsung Co-CEO Kyung Kye-hyun said earlier this year its foundry business would look for new clients in China, where it expects high market growth, as companies from automakers to appliance goods manufacturers rush to secure capacity to address persistent global chip shortages.

While Samsung is the first to production with 3-nanometer chip production, TSMC is planning 2-nanometer volume production in 2025.

Samsung is the market leader in memory chips, but it had been outspent by frontrunner TSMC in the more diverse foundry business, making it difficult to compete, analysts said.

"Non-memory is different, there's too much variety," said Kim Yang-jae, analyst at Daol Investment & Securities.

"There are only two kinds of memory chips - DRAM and NAND Flash. You can concentrate on one thing, raise efficiency and make a lot of it, but you can't do that with a thousand different non-memory chips."

Samsung's compound annual growth rate (CAGR) of capital spending between 2017 and 2023, which measures how quickly a company is increasing its investment, is estimated at 7.9%, versus TSMC's estimated 30.4%, according to Mirae Asset Securities.

Samsung's efforts to compete with the industry leader have also been hampered by less-than-expected yields of older chips during the past year or so, analysts said. The company said in March that its operations have shown a gradual improvement.



Meta Shares Skyrocket, Microsoft Slides on Wall Street after Earnings

A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
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Meta Shares Skyrocket, Microsoft Slides on Wall Street after Earnings

A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson
A Microsoft logo is seen a day after Microsoft Corp's $26.2 billion purchase of LinkedIn Corp, in Los Angeles, California, US, June 14, 2016. REUTERS/Lucy Nicholson

Shares in Meta skyrocketed by 10 percent at opening on Wall Street on Thursday, a day after the social media giant posted better than expected earnings as the company invests heavily in artificial intelligence.

Microsoft, whose earnings disappointed analysts, saw its share price tumble by 10 percent, with investors showing concern for the return on investment for the software giant's spending on AI.


Samsung Logs Best-ever Profit on AI Chip Demand

South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
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Samsung Logs Best-ever Profit on AI Chip Demand

South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File
South Korean tech giant Samsung Electronics posted record quarterly profits on Thursday, riding strong market demand for its artificial intelligence chips. Jung Yeon-je / AFP/File

South Korean tech giant Samsung Electronics posted record quarterly profits Thursday, riding massive market demand for the memory chips that power artificial intelligence.

A global frenzy to build AI data centers and develop the fast-evolving technology has sent orders for advanced high bandwidth memory microchips soaring.

That is also pushing up prices for less flashy chips used in consumer electronics -- threatening higher prices for phones, laptops and other devices worldwide.

In the quarter to December 2025, Samsung said it saw "its highest-ever quarterly consolidated revenue at KRW 93.8 trillion (US$65.5 billion)", a quarter-on-quarter increase of nine percent.

"Operating profit was also an all-time high, at KRW 20.1 trillion," the company said.

The dazzling earnings came a day after a key competitor, South Korean chip giant SK hynix, said operating profit had doubled last year to a record high, also buoyed by the AI boom.

The South Korean government has pledged to become one of the top three AI powers, behind the United States and China, with Samsung and SK hynix among the leading producers of high-performance memory.

Samsung said Thursday it expects "AI and server demand to continue increasing, leading to more opportunities for structural growth".

Annual revenue stood at 333.6 trillion won, while operating profit came in at 43.6 trillion won. Sales for the division that oversees its semiconductor business rose 33 percent quarter-on-quarter.

The company pointed to a $33.2 billion investment in chip production facilities -- pledging to continue spending in "transitioning to advanced manufacturing processes and upgrading existing production lines to meet rising demand".

- 'Clearly back' -

Major electronics manufacturers and industry analysts have warned that chipmakers focusing on AI sales will cause higher retail prices for consumer products across the board.

This week US chip firm Micron said it was building a $24 billion plant in Singapore in response to AI-driven demand that has caused a global shortage of memory components.

SK hynix announced Wednesday that its operating profit had doubled last year to a record 47.2 trillion won.

The company's shares have surged some 220 percent over the past six months, while Samsung Electronics has risen about 130 percent, part of a huge global tech rally fueled by optimism over AI.

Both companies are on the cusp of producing next-generation high-bandwidth "HBM4" chips for AI data centers, with Samsung reportedly due to start making them in February.

American chip giant Nvidia -- now the world's most valuable company -- is expected to be one of Samsung's customers for HBM4 chips.

But Nvidia has reportedly allocated around 70 percent of its HBM4 demand to SK hynix for 2026, up from the market's previous estimate of 50 percent.

"Samsung is clearly back and we are expecting them to show a significant turnaround with HBM4 for Nvidia's new products -- helping them move past last year's quality issues," Hwang Min-seong, research director at market analysis firm Counterpoint, told AFP.

But SK still "maintains a market lead in both quality and supply" of a number of key components, including Dynamic Random Access Memory chips used in AI servers, he said.

SK also this week said it will set up an "AI solutions firm" in the United States, committing $10 billion and weighing investments in US companies.


Google Unveils AI Tool Probing Mysteries of Human Genome

A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
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Google Unveils AI Tool Probing Mysteries of Human Genome

A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)
A Google logo is seen at a company research facility in Mountain View, California, US, May 13, 2025. (Reuters)

Google unveiled an artificial intelligence tool Wednesday that its scientists said would help unravel the mysteries of the human genome -- and could one day lead to new treatments for diseases.

The deep learning model AlphaGenome was hailed by outside researchers as a "breakthrough" that would let scientists study and even simulate the roots of difficult-to-treat genetic diseases.

While the first complete map of the human genome in 2003 "gave us the book of life, reading it remained a challenge", Pushmeet Kohli, vice president of research at Google DeepMind, told journalists.

"We have the text," he said, which is a sequence of three billion nucleotide pairs represented by the letters A, T, C and G that make up DNA.

However, "understanding the grammar of this genome -- what is encoded in our DNA and how it governs life -- is the next critical frontier for research," said Kohli, co-author of a new study in the journal Nature.

Only around two percent of our DNA contains instructions for making proteins, which are the molecules that build and run the body.

The other 98 percent was long dismissed as "junk DNA" as scientists struggled to understand what it was for.

However, this "non-coding DNA" is now believed to act like a conductor, directing how genetic information works in each of our cells.

These sequences also contain many variants that have been associated with diseases. It is these sequences that AlphaGenome is aiming to understand.

- A million letters -

The project is just one part of Google's AI-powered scientific work, which also includes AlphaFold, the winner of 2024's chemistry Nobel.

AlphaGenome's model was trained on data from public projects that measured non-coding DNA across hundreds of different cell and tissue types in humans and mice.

The tool is able to analyze long DNA sequences then predict how each nucleotide pair will influence different biological processes within the cell.

This includes whether genes start and stop and how much RNA -- molecules which transmit genetic instructions inside cells -- is produced.

Other models already exist that have a similar aim. However, they have to compromise, either by analyzing far shorter DNA sequences or decreasing how detailed their predictions are, known as resolution.

DeepMind scientist and lead study author Ziga Avsec said that long sequences -- up to a million DNA letters long -- were "required to understand the full regulatory environment of a single gene".

And the high resolution of the model allows scientists to study the impact of genetic variants by comparing the differences between mutated and non-mutated sequences.

"AlphaGenome can accelerate our understanding of the genome by helping to map where the functional elements are and what their roles are on a molecular level," study co-author Natasha Latysheva said.

The model has already been tested by 3,000 scientists across 160 countries and is open for anyone to use for non-commercial reasons, Google said.

"We hope researchers will extend it with more data," Kohli added.

- 'Breakthrough' -

Ben Lehner, a researcher at Cambridge University who was not involved in developing AlphaGenome but did test it, said the model "does indeed perform very well".

"Identifying the precise differences in our genomes that make us more or less likely to develop thousands of diseases is a key step towards developing better therapeutics," he explained.

However, AlphaGenome "is far from perfect and there is still a lot of work to do", he added.

"AI models are only as good as the data used to train them" and the existing data is not very suitable, he said.

Robert Goldstone, head of genomics at the UK's Francis Crick Institute, cautioned that AlphaGenome was "not a magic bullet for all biological questions".

This was partly because "gene expression is influenced by complex environmental factors that the model cannot see", he said.

However, the tool still represented a "breakthrough" that would allow scientists to "study and simulate the genetic roots of complex disease", Goldstone added.