Alorica, a company in Irvine, California, that runs customer-service centers around the world, has introduced an artificial intelligence translation tool that lets its representatives talk with customers who speak 200 different languages and 75 dialects.

So an Alorica representative who speaks, say, only Spanish can field a complaint about a balky printer or an incorrect bank statement from a Cantonese speaker in Hong Kong. Alorica wouldn’t need to hire a rep who speaks Cantonese.

Such is the power of AI. And, potentially, the threat: Perhaps companies won’t need as many employees — and will slash some jobs — if chatbots can handle the workload instead. But the thing is, Alorica isn’t cutting jobs. It’s still hiring aggressively.

The experience at Alorica — and at other companies, including furniture retailer IKEA — suggests that AI may not prove to be the job killer that many people fear. Instead, the technology might turn out to be more like breakthroughs of the past — the steam engine, electricity, the internet: That is, eliminate some jobs while creating others. And probably making workers more productive in general, to the eventual benefit of themselves, their employers and the economy.

Nick Bunker, an economist at the Indeed Hiring Lab, said he thinks AI “will affect many, many jobs — maybe every job indirectly to some extent. But I don’t think it’s going to lead to, say, mass unemployment. We have seen other big technological events in our history, and those didn’t lead to a large rise in unemployment. Technology destroys but also creates. There will be new jobs that come about.’’

At its core, artificial intelligence empowers machines to perform tasks previously thought to require human intelligence. The technology has existed in early versions for decades, having emerged with a problem-solving computer program, the Logic Theorist, built in the 1950s at what’s now Carnegie Mellon University. More recently, think of voice assistants like Siri and Alexa. Or IBM’s chess-playing computer, Deep Blue, which managed to beat the world champion Garry Kasparov in 1997.

AI burst into public consciousness in 2022 when OpenAI introduced ChatGPT, the generative AI tool that can conduct conversations, write computer code, compose music, craft essays and supply endless streams of information. The arrival of generative AI has raised worries that chatbots will replace freelance writers, editors, coders, telemarketers, customer service reps, paralegals and many more.

“AI is going to eliminate a lot of current jobs, and this is going to change the way that a lot of current jobs function,” Sam Altman, the CEO of OpenAI, said in a discussion at the Massachusetts Institute of Technology in May.

Yet the widespread assumption that AI chatbots will inevitably replace service workers, the way physical robots took many factory and warehouse jobs, isn’t becoming reality in any widespread way — not yet, anyway. And maybe it never will.

The White House Council of Economic Advisers said last month that it found “little evidence that AI will negatively impact overall employment.’’ The advisers noted that history shows technology typically makes companies more productive, speeding economic growth and creating new types of jobs in unexpected ways.

They cited a study this year led by David Autor, a leading MIT economist: It concluded that 60% of the jobs Americans held in 2018 didn’t even exist in 1940, having been created by technologies that emerged only later.

The outplacement firm Challenger, Gray & Christmas, which tracks job cuts, said it has yet to see much evidence of layoffs that can be attributed to labor-saving AI.

“I don’t think we’ve started seeing companies saying they’ve saved lots of money or cut jobs they no longer need because of this,’’ said Andy Challenger, who leads the firm’s sales team. “That may come in the future. But it hasn’t played out yet.’’

At the same time, the fear that AI poses a serious threat to some categories of jobs isn’t unfounded.

Consider Suumit Shah, an Indian entrepreneur who caused a uproar last year by boasting that he had replaced 90% of his customer support staff with a chatbot named Lina. The move at Shah’s company, Dukaan, which helps customers set up e-commerce sites, shrank the response time to an inquiry from 1 minute, 44 seconds to “instant.” It also cut the typical time needed to resolve problems from more than two hours to just over three minutes.

“It’s all about AI’s ability to handle complex queries with precision,” Mr. Shah said by email. The cost of providing customer support, he said, fell by 85%.

“Tough? Yes. Necessary? Absolutely,’’ Mr. hah posted on X.

Dukaan has expanded its use of AI to sales and analytics. “The tools,” Mr. Shah said, “keep growing more powerful.”

“It’s like upgrading from a Corolla to a Tesla,” he said. “What used to take hours now takes minutes. And the accuracy is on a whole new level.”

Similarly, researchers at Harvard Business School, the German Institute for Economic Research and London’s Imperial College Business School found in a study last year that job postings for writers, coders and artists tumbled within eight months of the arrival of ChatGPT.

A 2023 study by researchers at Princeton University, the University of Pennsylvania and New York University concluded that telemarketers and teachers of English and foreign languages held the jobs most exposed to ChatGPT-like language models. But being exposed to AI doesn’t necessarily mean losing your job to it. AI can also do the drudge work, freeing up people to do more creative tasks.

The Swedish furniture retailer IKEA, for example, introduced a customer-service chatbot in 2021 to handle simple inquiries. Instead of cutting jobs, IKEA retrained 8,500 customer-service workers to handle such tasks as advising customers on interior design and fielding complicated customer calls.

Chatbots can also be deployed to make workers more efficient, complementing their work rather than eliminating it. A study by Erik Brynjolfsson of Stanford University and Danielle Li and Lindsey Raymond of MIT tracked 5,200 customer-support agents at a Fortune 500 company who used a generative AI-based assistant. The AI tool provided valuable suggestions for handling customers. It also supplied links to relevant internal documents.

Those who used the chatbot, the study found, proved 14% more productive than colleagues who didn’t. They handled more calls and completed them faster. The biggest productivity gains — 34% — came from the least-experienced, least-skilled workers.

At an Alorica call center in Albuquerque, New Mexico, one customer-service rep had been struggling to gain access to the information she needed to quickly handle calls. After Alorica trained her to use AI tools, her “handle time’’ — how long it takes to resolve customer calls — fell in four months by an average of 14 minutes a call to just over seven minutes.

Over a period of six months, the AI tools helped one group of 850 Alorica reps reduce their average handle time to six minutes, from just over eight minutes. They can now field 10 calls an hour instead of eight — an additional 16 calls in an eight-hour day.

Alorica agents can use AI tools to quickly access information about the customers who call in — to check their order history, say, or determine whether they had called earlier and hung up in frustration.

Suppose, said Mike Clifton, Alorica’s co-CEO, a customer complains that she received the wrong product. The agent can “hit replace, and the product will be there tomorrow,” he said. ” ‘Anything else I can help you with? No?’ Click. Done. Thirty seconds in and out.’’

Now the company is beginning to use its Real-time Voice Language Translation tool, which lets customers and Alorica agents speak and hear each other in their own languages.

“It allows (Alorica reps) to handle every call they get,” said Rene Paiz, a vice president of customer service. “I don’t have to hire externally’’ just to find someone who speaks a specific language.

Yet Alorica isn’t cutting jobs. It continues to seek hires — increasingly, those who are comfortable with new technology.

“We are still actively hiring,’’ Ms. Paiz says. “We have a lot that needs to be done out there.’’

Alorica, a company in Irvine, California, that runs customer-service centers around the world, has introduced an artificial intelligence translation tool that lets its representatives talk with customers who speak 200 different languages and 75 dialects.

So an Alorica representative who speaks, say, only Spanish can field a complaint about a balky printer or an incorrect bank statement from a Cantonese speaker in Hong Kong. Alorica wouldn’t need to hire a rep who speaks Cantonese.

Such is the power of AI. And, potentially, the threat: Perhaps companies won’t need as many employees — and will slash some jobs — if chatbots can handle the workload instead. But the thing is, Alorica isn’t cutting jobs. It’s still hiring aggressively.

The experience at Alorica — and at other companies, including furniture retailer IKEA — suggests that AI may not prove to be the job killer that many people fear. Instead, the technology might turn out to be more like breakthroughs of the past — the steam engine, electricity, the internet: That is, eliminate some jobs while creating others. And probably making workers more productive in general, to the eventual benefit of themselves, their employers and the economy.

Nick Bunker, an economist at the Indeed Hiring Lab, said he thinks AI “will affect many, many jobs — maybe every job indirectly to some extent. But I don’t think it’s going to lead to, say, mass unemployment. We have seen other big technological events in our history, and those didn’t lead to a large rise in unemployment. Technology destroys but also creates. There will be new jobs that come about.’’

At its core, artificial intelligence empowers machines to perform tasks previously thought to require human intelligence. The technology has existed in early versions for decades, having emerged with a problem-solving computer program, the Logic Theorist, built in the 1950s at what’s now Carnegie Mellon University. More recently, think of voice assistants like Siri and Alexa. Or IBM’s chess-playing computer, Deep Blue, which managed to beat the world champion Garry Kasparov in 1997.

AI burst into public consciousness in 2022 when OpenAI introduced ChatGPT, the generative AI tool that can conduct conversations, write computer code, compose music, craft essays and supply endless streams of information. The arrival of generative AI has raised worries that chatbots will replace freelance writers, editors, coders, telemarketers, customer service reps, paralegals and many more.

“AI is going to eliminate a lot of current jobs, and this is going to change the way that a lot of current jobs function,” Sam Altman, the CEO of OpenAI, said in a discussion at the Massachusetts Institute of Technology in May.

Yet the widespread assumption that AI chatbots will inevitably replace service workers, the way physical robots took many factory and warehouse jobs, isn’t becoming reality in any widespread way — not yet, anyway. And maybe it never will.

The White House Council of Economic Advisers said last month that it found “little evidence that AI will negatively impact overall employment.’’ The advisers noted that history shows technology typically makes companies more productive, speeding economic growth and creating new types of jobs in unexpected ways.

They cited a study this year led by David Autor, a leading MIT economist: It concluded that 60% of the jobs Americans held in 2018 didn’t even exist in 1940, having been created by technologies that emerged only later.

The outplacement firm Challenger, Gray & Christmas, which tracks job cuts, said it has yet to see much evidence of layoffs that can be attributed to labor-saving AI.

“I don’t think we’ve started seeing companies saying they’ve saved lots of money or cut jobs they no longer need because of this,’’ said Andy Challenger, who leads the firm’s sales team. “That may come in the future. But it hasn’t played out yet.’’

At the same time, the fear that AI poses a serious threat to some categories of jobs isn’t unfounded.

Consider Suumit Shah, an Indian entrepreneur who caused a uproar last year by boasting that he had replaced 90% of his customer support staff with a chatbot named Lina. The move at Shah’s company, Dukaan, which helps customers set up e-commerce sites, shrank the response time to an inquiry from 1 minute, 44 seconds to “instant.” It also cut the typical time needed to resolve problems from more than two hours to just over three minutes.

“It’s all about AI’s ability to handle complex queries with precision,” Mr. Shah said by email. The cost of providing customer support, he said, fell by 85%.

“Tough? Yes. Necessary? Absolutely,’’ Mr. hah posted on X.

Dukaan has expanded its use of AI to sales and analytics. “The tools,” Mr. Shah said, “keep growing more powerful.”

“It’s like upgrading from a Corolla to a Tesla,” he said. “What used to take hours now takes minutes. And the accuracy is on a whole new level.”

Similarly, researchers at Harvard Business School, the German Institute for Economic Research and London’s Imperial College Business School found in a study last year that job postings for writers, coders and artists tumbled within eight months of the arrival of ChatGPT.

A 2023 study by researchers at Princeton University, the University of Pennsylvania and New York University concluded that telemarketers and teachers of English and foreign languages held the jobs most exposed to ChatGPT-like language models. But being exposed to AI doesn’t necessarily mean losing your job to it. AI can also do the drudge work, freeing up people to do more creative tasks.

The Swedish furniture retailer IKEA, for example, introduced a customer-service chatbot in 2021 to handle simple inquiries. Instead of cutting jobs, IKEA retrained 8,500 customer-service workers to handle such tasks as advising customers on interior design and fielding complicated customer calls.

Chatbots can also be deployed to make workers more efficient, complementing their work rather than eliminating it. A study by Erik Brynjolfsson of Stanford University and Danielle Li and Lindsey Raymond of MIT tracked 5,200 customer-support agents at a Fortune 500 company who used a generative AI-based assistant. The AI tool provided valuable suggestions for handling customers. It also supplied links to relevant internal documents.

Those who used the chatbot, the study found, proved 14% more productive than colleagues who didn’t. They handled more calls and completed them faster. The biggest productivity gains — 34% — came from the least-experienced, least-skilled workers.

At an Alorica call center in Albuquerque, New Mexico, one customer-service rep had been struggling to gain access to the information she needed to quickly handle calls. After Alorica trained her to use AI tools, her “handle time’’ — how long it takes to resolve customer calls — fell in four months by an average of 14 minutes a call to just over seven minutes.

Over a period of six months, the AI tools helped one group of 850 Alorica reps reduce their average handle time to six minutes, from just over eight minutes. They can now field 10 calls an hour instead of eight — an additional 16 calls in an eight-hour day.

Alorica agents can use AI tools to quickly access information about the customers who call in — to check their order history, say, or determine whether they had called earlier and hung up in frustration.

Suppose, said Mike Clifton, Alorica’s co-CEO, a customer complains that she received the wrong product. The agent can “hit replace, and the product will be there tomorrow,” he said. ” ‘Anything else I can help you with? No?’ Click. Done. Thirty seconds in and out.’’

Now the company is beginning to use its Real-time Voice Language Translation tool, which lets customers and Alorica agents speak and hear each other in their own languages.

“It allows (Alorica reps) to handle every call they get,” said Rene Paiz, a vice president of customer service. “I don’t have to hire externally’’ just to find someone who speaks a specific language.

Yet Alorica isn’t cutting jobs. It continues to seek hires — increasingly, those who are comfortable with new technology.

“We are still actively hiring,’’ Ms. Paiz says. “We have a lot that needs to be done out there.’’

It’s a small casual gathering. But the men are not here for campfires and nature hikes in the surrounding mountains and woods. Instead, these pioneers are about to embark on an experimental journey that will spark countless debates for decades to come and change not just the course of technology – but the course of humanity.

Welcome to the Dartmouth Conference – the birthplace of artificial intelligence (AI) as we know it today.

What transpired here would ultimately lead to ChatGPT and the many other kinds of AI which now help us diagnose disease, detect fraud, put together playlists and write articles (well, not this one). But it would also create some of the many problems the field is still trying to overcome. Perhaps by looking back, we can find a better way forward.

The summer that changed everything

In the mid-1950s, rock’n’roll was taking the world by storm. Elvis’s Heartbreak Hotel was topping the charts, and teenagers started embracing James Dean’s rebellious legacy.

But in 1956, in a quiet corner of New Hampshire, a different kind of revolution was happening.

The Dartmouth Summer Research Project on Artificial Intelligence, often remembered as the Dartmouth Conference, kicked off on June 18 and lasted for about eight weeks. It was the brainchild of four American computer scientists – John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon – and brought together some of the brightest minds in computer science, mathematics and cognitive psychology at the time.

These scientists, along with some of the 47 people they invited, set out to tackle an ambitious goal: to make intelligent machines.

As McCarthy put it in the conference proposal, they aimed to find out “how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans”.

The birth of a field – and a problematic name

The Dartmouth Conference didn’t just coin the term “artificial intelligence”; it coalesced an entire field of study. It’s like a mythical Big Bang of AI – everything we know about machine learning, neural networks and deep learning now traces its origins back to that summer in New Hampshire.

But the legacy of that summer is complicated.

Artificial intelligence won out as a name over others proposed or in use at the time. Shannon preferred the term “automata studies”, while two other conference participants (and the soon-to-be creators of the first AI program), Allen Newell and Herbert Simon, continued to use “complex information processing” for a few years still.

But here’s the thing: having settled on AI, no matter how much we try, today we can’t seem to get away from comparing AI to human intelligence.

This comparison is both a blessing and a curse.

On the one hand, it drives us to create AI systems that can match or exceed human performance in specific tasks. We celebrate when AI outperforms humans in games such as chess or Go, or when it can detect cancer in medical images with greater accuracy than human doctors.

On the other hand, this constant comparison leads to misconceptions.

When a computer beats a human at Go, it is easy to jump to the conclusion that machines are now smarter than us in all aspects – or that we are at least well on our way to creating such intelligence. But AlphaGo is no closer to writing poetry than a calculator.

And when a large language model sounds human, we start wondering if it is sentient.

But ChatGPT is no more alive than a talking ventriloquist’s dummy.

The overconfidence trap

The scientists at the Dartmouth Conference were incredibly optimistic about the future of AI. They were convinced they could solve the problem of machine intelligence in a single summer.

This overconfidence has been a recurring theme in AI development, and it has led to several cycles of hype and disappointment.

Simon stated in 1965 that “machines will be capable, within 20 years, of doing any work a man can do”. Minsky predicted in 1967 that “within a generation, […] the problem of creating ‘artificial intelligence’ will substantially be solved”.

Popular futurist Ray Kurzweil now predicts it’s only five years away: “We’re not quite there, but we will be there, and by 2029 it will match any person”.

Reframing our thinking: new lessons from Dartmouth

So, how can AI researchers, AI users, governments, employers and the broader public move forward in a more balanced way?

A key step is embracing the differences and utility of machine systems. Instead of focusing on the race to “artificial general intelligence”, we can focus on the unique strengths of the systems we have built – for example, the enormous creative capacity of image models.

Shifting the conversation from automation to augmentation is also important. Rather than pitting humans against machines, let’s focus on how AI can assist and augment human capabilities.

Let’s also emphasise ethical considerations. The Dartmouth participants didn’t spend much time discussing the ethical implications of AI. Today, we know better, and must do better.

We must also refocus research directions. Let’s emphasise research into AI interpretability and robustness, interdisciplinary AI research and explore new paradigms of intelligence that aren’t modelled on human cognition.

Finally, we must manage our expectations about AI. Sure, we can be excited about its potential. But we must also have realistic expectations so that we can avoid the disappointment cycles of the past.

As we look back at that summer camp 68 years ago, we can celebrate the vision and ambition of the Dartmouth Conference participants. Their work laid the foundation for the AI revolution we’re experiencing today.

By reframing our approach to AI – emphasising utility, augmentation, ethics and realistic expectations – we can honour the legacy of Dartmouth while charting a more balanced and beneficial course for the future of AI.

After all, real intelligence lies not just in creating smart machines, but in how wisely we choose to use and develop them.

Sandra Peter, Director of Sydney Executive Plus, University of Sydney

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Mumbai:

Granting relief to composer-singer Arijit Singh, the Bombay High Court has said AI tools generating content using a celebrity’s voice, image or other attributes without consent violate his or her “personality rights”.

Celebrities are particularly vulnerable to unauthorised generation of content through AI tools, the court said.

Hearing a petition filed by the famous singer, Justice R I Chagla in his interim order on July 26 restrained eight online platforms from using Singh’s “personality rights”, and directed them to remove all such content and also voice conversion tools.

The singer had moved the court claiming that these platforms provide AI tools to synthesize artificial sound recordings by mimicking his voice, mannerisms and other attributes.

Arijit Singh has consciously refrained from any kind of brand endorsement or gross commercialization of his personality traits for the past several years, his lawyer Hiren Kamod said.

The high court agreed that Singh should be given interim relief.

“What shocks the conscience of this court is the manner in which celebrities, particularly performers such as the present plaintiff are vulnerable to being targeted by unauthorized generative AI content,” the judge said.

The freedom of speech and expression allows for critique and commentary but does not grant the license to exploit a celebrity’s persona for commercial gain, Justice Chagla said.

“Making AI tools available that enable the conversion of any voice into that of a celebrity without his/her permission constitutes a violation of the celebrity’s personality rights,” it added.

Such tools facilitate “unauthorized appropriation and manipulation” of a celebrity’s voice, a key component of their personal identity, Justice Chagla said.

Further, such use of the AI technology also undermines celebrities’ ability to prevent “deceptive uses of their identity,” the HC said.

Such platforms are emboldening Internet users to create counterfeit sound recordings and videos, it observed.

Singh has gained immense goodwill and reputation over the course of a very successful career, the judge noted.

“Prima facie, I am of the view that the plaintiff’s personality traits including his name, voice, photograph/ caricature, image, likeness, persona and other attributes of his personality are protectable elements of his personality rights,” Justice Chagla said.

Advocate Kamod told the court that Arijit Singh hails from a small town and has humble beginnings, and now he is one of the most celebrated singers in the world.

The petition, filed through Legasis Partners, sought protection of his personality rights with regard to his name, voice, signatures, photograph, image, caricature, likeness, persona, and various other attributes of his personality against unauthorized/unlicensed commercial exploitation and misuse.

Several YouTube channels were creating memes and GIFs “causing ridicule, embarrassment and humiliation” and affecting the singer’s reputation, it said.

(This story has not been edited by NDTV staff and is auto-generated from a syndicated feed.)

Japanese eSports gamer Mashiro is blind and often relies on a companion to get around Tokyo — but he hopes that artificial intelligence, hailed as a promising tool for people with disabilities, can help him travel alone.

The 26-year-old ‘Street Fighter’ player put the latest version of AI chatbot ChatGPT to the test on his way to a stadium for a recent Para eSports meet-up.

“I can’t participate in an event like this without someone to rely on,” he told AFP. “Also, sometimes I just want to get around by myself without speaking to other people.

“So if I can use technology like ChatGPT to design my own special needs support, that would be great.”

This year, the US firm OpenAI, released GPT-4o, which understands voice, text and image commands in several languages.

The generative gadget, along with others such as Google’s Gemini, is part of a fast-growing field that experts say could make education, employment and everyday services more accessible.

Following the streets’ tactile paving, Masahiro Fujimoto – who goes by his online handle Mashiro – used his stick adorned with a small monkey mascot to find his way from the station.

As he went, he spoke to GPT-4o like a friend, receiving its answers through an earpiece in one ear, leaving the other side free to listen out for cars.

Having asked for basic directions, he added: “In fact, I am blind, so could you give me further details for blind people?”

“Of course,” the bot replied. “You might notice an increase in crowd noise and the sound of activities as you get closer.”

The journey, 20 minutes for sighted people, took Mashiro around four times as long with several U-turns.

When it started to rain heavily, he requested help from his friend, who is partially sighted, to finish the journey.

“Arrival!” finally shouted Mashiro, who has microphthalmos and has been blind since birth, using only sound to demolish his opponents on ‘Street Fighter 6’.

AI can cater to specific needs better than “one-size-fits-all” assistive products and technologies, said Youngjun Cho, an associate professor in computer science at University College London (UCL).

“Its potential is enormous,” said Cho, who also works at UCL’s Global Disability Innovation Hub.

“I envisage that this can empower many individuals and promote independence.”

People with hearing loss can, for example, use AI speech-to-text transcription, while chatbots can help format a resume for someone with learning disabilities.

Some tools for visually impaired people, such as Seeing AI, Envision AI and TapTapSee, describe phone camera images.

Danish app Be My Eyes, where real-life volunteers help via live chat, is working with OpenAI to develop a “digital visual assistant”.

But Masahide Ishiki, a Japanese expert in disability and digital accessibility, warned it can be “tricky” to catch mistakes from ChatGPT, which “replies so naturally”.

“The next objective (for generative AI) is to improve the accuracy of real-time visual recognition, to ultimately reach capabilities close to that of a human eye,” said Ishiki, who is blind.

Marc Goblot of the Tech for Disability group also cautioned that AI is trained on “very mainstream datasets” which are “not representative of the full spectrum of people’s perceptions and especially the margins”.

Mashiro said ChatGPT’s limited recognition of Japanese words and locations made his AI-assisted journey more challenging.

Although the experiment was “a lot of fun”, it would have been easier if ChatGPT was connected to a map tool, said the gamer, who travelled around Europe last year using Google Maps and help from those around him.

He has already decided on his next travel destination: Yakushima rainforest island in southern Japan.

“I want to experience whatever happens when travelling somewhere like that,” he said.

Reserve Bank of India Governor Shaktikanta Das. File
| Photo Credit: PTI

RBI Governor Shaktikanta Das on Friday emphasised on the need to eliminate biases in algorithms as the use of artificial intelligence (AI) and machine learning (ML) is on the rise.

Delivering the inaugural address at the 18th Statistics Day Conference organised by the RBI, he said the use of statistics had been ever growing as a preferred tool for drawing inferences in diverse fields and the discipline had moved beyond collection of facts to focusing more on interpretation and drawing inferences, taking into account the level of uncertainty.

The Reserve Bank of India (RBI) has ventured into AI/ML analytics in multiple areas. Under the RBI’s aspirational goals for RBI@100, Mr. Das said the central bank was aiming to develop cutting-edge systems for high frequency and real-time data monitoring and analysis.

For a few days, AI chip juggernaut Nvidia sat on the throne as the world’s biggest company, but behind its staggering success are questions on whether new entrants can stake a claim to the artificial intelligence bonanza.

Nvidia, which makes the processors that are the only option to train generative AI’s large language models, is now Big Tech’s newest member and its stock market takeoff has lifted the whole sector.

Even tech’s second rung on Wall Street has ridden on Nvidia’s coattails with Oracle, Broadcom, HP and a spate of others seeing their stock valuations surge, despite sometimes shaky earnings.

Amid the champagne popping, startups seeking the attention of Silicon Valley venture capitalists are being asked to innovate — but without a clear indication of where the next chapter of AI will be written.

When it comes to generative AI, doubts persist on what exactly will be left for companies that are not existing model makers, a field dominated by Microsoft-backed OpenAI, Google and Anthropic.

Most agree that competing with them head-on could be a fool’s errand.

“I don’t think that there’s a great opportunity to start a foundational AI company at this point in time,” said Mike Myer, founder and CEO of tech firm Quiq, at the Collision technology conference in Toronto.

Some have tried to build applications that use or mimic the powers of the existing big models, but this is being slapped down by Silicon Valley’s biggest players.

“What I find disturbing is that people are not differentiating between those applications which are roadkill for the models as they progress in their capabilities, and those that are really adding value and will be here 10 years from now,” said venture capital veteran Vinod Khosla.

– ‘Won’t keep up’ –

The tough-talking Khosla is one of OpenAI’s earliest investors.

“Grammarly won’t keep up,” Khosla predicted of the spelling and grammar checking app, and others similar to it.

He said these companies, which put only a “thin wrapper” around what the AI models can offer, are doomed.

One of the fields ripe for the taking is chip design, Khosla said, with AI demanding ever more specialized processors that provide highly specific powers.

“If you look across the chip history, we really have for the most part focused on more general chips,” Rebecca Parsons, CTO at tech consultancy Thoughtworks, told AFP.

Providing more specialized processing for the many demands of AI is an opportunity seized by Groq, a hot startup that has built chips for the deployment of AI as opposed to its training, or inference — the specialty of Nvidia’s world-dominating GPUs.

Groq CEO Jonathan Ross told AFP that Nvidia won’t be the best at everything, even if they are uncontested for generative AI training.

“Nvidia and (its CEO) Jensen Huang are like Michael Jordan… the greatest of all time in basketball. But inference is baseball, and we try and forget the time where Michael Jordan tried to play baseball and wasn’t very good at it,” he said.

Another opportunity will come from highly specialized AI that will provide expertise and know-how based on proprietary data which won’t be co-opted by voracious big tech.

“Open AI and Google aren’t going to build a structural engineer. They’re not going to build products like a primary care doctor or a mental health therapist,” said Khosla.

Profiting from highly specialized data is the basis of Cohere, another of Silicon Valley’s hottest startups that pitches specifically-made models to businesses that are skittish about AI veering out of their control.

“Enterprises are skeptical of technology, and they’re risk-averse, and so we need to win their trust and to prove to them that there’s a way to adopt this technology that’s reliable, trustworthy and secure,” Cohere CEO Aidan Gomez told AFP.

When he was just 20 and working at Google, Gomez co-authored the seminal paper “Attention Is All You Need,” which introduced Transformer, the architecture behind popular large language models like OpenAI’s GPT-4.

The company has received funding from Nvidia and Salesforce Ventures and is valued in the billions of dollars.

(This story has not been edited by NDTV staff and is auto-generated from a syndicated feed.)

Oil tanker SCF Primorye, owned by Russian state shipping company Sovcomflot, transits the Bosphorus in Istanbul, Turkey, April 29, 2024.
| Photo Credit: Reuters

The global commercial shipping industry could cut down its carbon emissions by 47 million tonnes per year by deploying artificial intelligence for sea navigation, a study by autonomous shipping startup Orca AI showed on Tuesday.

The use of the technology could reduce the need for maneuvers and route deviation from close encounters with high-risk marine targets such as vessels, buoys and sea mammals by alerting the crew in real time, according to the report.

Why it is important?

Shipping, responsible for moving about 90% of global trade, contributes nearly 3% to the world’s carbon dioxide emissions. This share is anticipated to rise in the coming years unless stricter pollution control measures are implemented.

The International Maritime Organization aims to cut emissions by 20% by 2030, a target under threat from the ongoing Red Sea crisis.

Key Quote

“In the short term, it can lead to fewer crew members on the bridge, while those who are on the bridge will have a reduced workload and more attention to tackle complex navigational tasks, optimizing the voyage and reducing fuel and emissions,” Orca AI CEO Yarden Gross told Reuters.

“In the long term, it will open the door to fully autonomous shipping.”

Context

Global carbon dioxide shipping emissions reached an estimated 858 million tonnes in 2022, a marginal rise from the previous year, according to the Organization for Economic Cooperation and Development.

An average of 2,976 marine incidents are reported per year, Orca AI’s study showed.

By the numbers

The reduction in route deviations could help ships shave off 38.2 million nautical miles per year from their travel, saving an average of $100,000 in fuel costs per vessel, according to Orca AI’s report.

AI could also lower close encounters by 33% in open waters, it said.

New Delhi:

Amid consternation and outrage over a series of deepfake videos, actor Alia Bhatt has fallen prey to the technology yet again.

Alia Bhatt’s new deepfake shows her taking part in the ‘get ready with me’ trend in a video shared on Instagram. The video shows her getting ready in a black kurta and putting the makeup on.

This is not the first time that a deepfake video of Alia has gone viral on social media.

Earlier, a deepfake video of Alia Bhatt’s face merged with actor Wamiqa Gabbi’s had also gone viral. Her another deepfake showed a woman with the morphed face of Alia Bhatt making obscene gestures.

Several Instagram users have reacted to Alia Bhatt’s deepfake video expressing concern over the misuse of Artificial Intelligence (AI).

“AI is getting dangerous day by day,” a user said. A second user said, “I am getting scared of AI now.” “I really hope you have consent for using the AI that uses real human faces,” said another Alia Bhatt friend.

Deepfakes are a form of synthetic media crafted using artificial intelligence, employing sophisticated algorithms to manipulate both visual and audio elements.

Deepfakes of several celebrities – including Rashmika Mandanna, Kajol, Katrina Kaif, Aamir Khan, Ranveer Singh and Sara Tendulkar – had earlier surfaced on the internet.

The government has advised all intermediaries – referring to social media platforms like Instagram and X – to ensure users “do not violate the prohibited content” rule of the IT Act, as it bids to combat the worrying trend of deepfakes.

The Centre has said that the creation and circulation of deepfakes carry a strong penalty Rs 1 lakh in fine and three years in jail.

Prime Minister Narendra Modi had also flagged the misuse of AI for creating deepfake videos and called it a “big concern.” “During the times of Artificial Intelligence, it is important that technology should be used responsibly,” he cautioned.

Whitney Wolfe Herd, founder of the dating app Bumble, said that artificial intelligence (AI) could revolutionise the way people connect online.

Speaking at Bloomberg Tech in San Francisco, Ms Herd said that the women-focused dating app is embracing AI. She added that the use of AI is necessary “to help create healthier and more equitable” dating experiences.

Talking about why the involvement of AI is necessary, Ms Herd said that “dating is exhausting” and she wishes Bumble to be “the best place on the internet for women”.

She also gave an insight into how modern dating could look like with the growing use of AI. Ms Herd also admitted to the fact that a person could be talking to an “AI dating concierge” in future.

Ms Herd added, “Loneliness is actually killing us. And social media, while it has its benefits, it is not social media. It is anti-social media. So I think there is something really powerful about the technology that we are building to really connect us, go online, to get offline. And that is going to be absolutely critical for the next generation, the current generation, and for bringing us closer together.”

Talking about women making first move through Bumble, Ms Herd said, “What we heard from over 70 per cent of the women that we spoke to was ‘we love making the first move, but we don’t love how we make the first move.’ Sending a message to 70 matches is exhausting. Women already have so much work every day. We kept talking to all these women of all ages. They are like ‘Dating is exhausting’.”

Ms Herd said, “So we heard from them that we wanted to preserve the safety and the original inspiration behind making the first move, which was to put women in the driver’s seat and also to remove a lot of rejection from men. Dating was a broken system.”

She added that Bumble’s new CEO Lidiane Jones will help in making way for AI integration in the app.

Ms Heard added, “We are obsessed with our customers. For several years, I read every single email. They went to my phone. I was the feedback person. So no one realised that the CEO was responding to them. I was essentially the first line of communication. And we still do that. And so what we are doing is we are leaning into the things people don’t like, the things that are stressing them. And we are saying, how do we be the best place on the internet for women? So with Lidiane’s expertise in AI and her unbelievable technology background, we are just going to innovate.”

On Bumble’s future with AI’s involvement, Ms Herd said, “If you want to get really out there, there is a world where your [AI] dating concierge could go and date for you with other dating concierges.”

She added, “No. No. Truly. And then you don’t have to talk to 600 people. It could scan all of San Francisco for you and say, ‘These are the three people you really ought to meet.’ And so that is the power of AI if harnessed the right way.”