AI Chatbots Must Learn to Say 'Help!' Says Microsoft Exec

A Microsoft logo is seen in Los Angeles, California US November 7, 2017. (Reuters)
A Microsoft logo is seen in Los Angeles, California US November 7, 2017. (Reuters)
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AI Chatbots Must Learn to Say 'Help!' Says Microsoft Exec

A Microsoft logo is seen in Los Angeles, California US November 7, 2017. (Reuters)
A Microsoft logo is seen in Los Angeles, California US November 7, 2017. (Reuters)

Generative AI tools will save companies lots of time and money, promises Vik Singh, a Microsoft vice president, even if the models must learn to admit when they just don't know what to do.
"Just to be really frank, the thing that's really missing today is that a model doesn't raise its hands and say 'Hey, I'm not sure, I need help,'" Singh told AFP in an interview.
Since last year, Microsoft, Google and their competitors have been rapidly deploying generative AI applications like ChatGPT, which produce all kinds of content on demand and give users the illusion of omniscience.
But despite progress, they still "hallucinate," or invent answers.
This is an important problem for the Copilot executive to solve: Singh's corporate customers can't afford for their AI systems to go off the rails, even occasionally.
Marc Benioff, CEO of Salesforce, this week said he saw many of his customers increasingly frustrated with the meanderings of Microsoft's Copilot.
Singh insisted that "really smart people" were trying to find ways for a chatbot to admit "when it doesn't know the right answer and to ask for help."
'Real savings'
A more humble model would be no less useful, in Singh's opinion. Even if the model has to turn to a human in 50 percent of cases, that still saves "tons of money."
At one Microsoft client, "every time a new request comes in, they spend $8 to have a customer service rep answer it, so there are real savings to be had, and it's also a better experience for the customer because they get a faster response."
Singh arrived at Microsoft in January and this summer took over as head of the teams developing "Copilot," Microsoft's AI assistant that specializes in sales, accounting and online services.
These applications have the gargantuan task of bringing in revenue and justifying the massive investments in generative AI.
At the height of the AI frenzy, start-ups driving the technology were promising systems so advanced that they would "uplift humanity," in the words of Sam Altman, head of OpenAI, which is mainly funded by Microsoft.
But for the time being, the new technology is mainly used to boost productivity, and hopefully profits.
According to Microsoft, Copilot can do research for salespeople, freeing up time to call customers. Lumen, a telecom company, "saves around $50 million a year" doing this, said Singh.
Singh's teams are working on integrating Copilot directly into the tech giant's software and making it more autonomous.
"Let's say I'm a sales rep and I have a customer call," suggested the executive. Two weeks later, the model can "nudge the rep to go follow up, or better, just go and automatically send the email on the rep's behalf because it's been approved to do so."
'First inning'
In other words, before finding a solution to global warming, AI is expected to rid humanity of boring, repetitive chores.
"We're in the first inning," Singh said. "A lot of these things are productivity based, but they obviously have huge benefits."
Will all these productivity gains translate into job losses?
Leaders of large firms, such as K Krithivasan, boss of Indian IT giant TCS, have declared that generative AI will all but wipe out call centers.
But Singh, like many Silicon Valley executives, is counting on technology to make humans more creative and even create new jobs.
He pointed to his experience at Yahoo in 2008, when a dozen editors chose the articles for the home page.
"We came up with the idea of using AI to optimize this process, and some people asked 'Oh my God, what's going to happen to the employees?'" said Singh.
The automated system made it possible to renew content more quickly, thereby increasing the number of clicks on links but also the need for new articles.
"In the end," said the executive, "we had to recruit more editors."



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.


Hong Kong Scientists Launch AI Model to Better Predict Extreme Weather

A general view of Two International Finance Centre (IFC), HSBC headquarters and Bank of China in Hong Kong, China July 13, 2021. (Reuters)
A general view of Two International Finance Centre (IFC), HSBC headquarters and Bank of China in Hong Kong, China July 13, 2021. (Reuters)
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Hong Kong Scientists Launch AI Model to Better Predict Extreme Weather

A general view of Two International Finance Centre (IFC), HSBC headquarters and Bank of China in Hong Kong, China July 13, 2021. (Reuters)
A general view of Two International Finance Centre (IFC), HSBC headquarters and Bank of China in Hong Kong, China July 13, 2021. (Reuters)

A team of Hong Kong scientists has developed an artificial intelligence weather-forecasting system to predict thunderstorms and heavy downpours up to four hours ahead, ​compared with the range of 20 minutes to two hours now.

The system will help governments and emergency services respond more effectively to increasingly frequent extremes of weather linked to climate change, the team from Hong Kong University of Science and Technology said on Wednesday.

"We hope to use AI and satellite data to improve prediction of extreme weather ‌so we can ‌be better prepared," said Su ‌Hui, chair ⁠professor ​of ‌the university's civil and environmental engineering department, who led the project.

The system aimed to predict heavy rainfall, Su told a press conference to describe the work published in the Proceedings of the National Academy of Sciences in December.

Its model applies generative AI techniques, injecting noise into training data so that the ⁠system learns to reverse the process in the effort to produce more ‌precise forecasts.

Developed in collaboration with China’s ‍weather authorities, it refreshes forecasts ‍every 15 minutes and has boosted accuracy by more ‍than 15%, the team said.

Such work is crucial because the number of typhoons and episodes of wet weather Hong Kong and much of southern China faced in 2025 far exceeded the seasonal ​norm, scientists said.

The city issued its highest rainstorm warning five times last year and the second ⁠highest 16 times, setting new records, its observatory said.

Both China's Meteorological Administration and Hong Kong's Observatory are working to incorporate the model into forecasts.

The team's new AI framework, called the Deep Diffusion Model based on Satellite Data (DDMS), was trained using infrared brightness temperature data collected between 2018 and 2021 by China’s Fengyun-4 satellite.

Satellites can detect cloud formation earlier than other forecasting systems such as radar, Su added.

The data was combined with meteorological expertise to capture the evolution of convective cloud ‌systems and later validated with spring and summer samples from 2022 and 2023.