With 2.5 billion prompts a day, is ChatGPT becoming the new Google?
In a recent essay, Altman described the AI industry as building 'a brain for the world.' He added that intelligence 'too cheap to meter is well within grasp.'Sam Altman is also reportedly scheduled to visit Washington, DC this week to push a broader message: that AI should remain a democratic force, accessible to everyone. According to Axios, Altman plans to present a 'third path' between over-optimism and fear-driven doomerism around AI's impact on jobs at a major Federal Reserve conference soon. - EndsTrending Reel
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Indian Express
11 minutes ago
- Indian Express
Weapons of Math Destruction: What do Olympiad gold medals mean for the AI race?
Large language models (LLMs) are widely known for their ability to churn out essays and other forms of text in seconds. But for years, researchers have been using math problems that involve advanced reasoning as a test of what artificial intelligence (AI) systems are truly capable of. The race to build AI systems that rival human intelligence has led to several claims of mathematical breakthroughs, along with questions about the validity of certain benchmark tests. But this week provided a clearer sign of progress, as two AI models – developed by OpenAI and Google DeepMind – achieved scores high enough to win gold medals at the International Math Olympiad (IOM) 2025, a prestigious math competition for high school students. This is the first time any AI model has achieved such a high level of success on these kinds of problems. Every year since 1959, countries from around the world send their brightest 'mathletes' to compete at the IMO. The Olympiad takes place in two sessions, and participants are expected to solve three challenging math problems in each session. The duration of each session is 4.5 hours. The AI models solved five out of six math problems under the same conditions as human participants. Each problem carries seven points. They cover topics such as algebra, combinatorics, geometry, and number theory. The two AI models scored 35 out of 42 points, which was the cut-off this year for winning a gold medal. Both OpenAI and Google DeepMind used experimental AI reasoning models. Reasoning models are different from LLMs because they are said to work through a problem step-by-step before finally arriving at an answer. India also bagged three gold medals, two silver, and one bronze at IOM 2025. Among the three gold-medal winners were Kanav Talwar and Aarav Gupta from Delhi Public School (DPS) Faridabad, while their schoolmate Archit Manas took home the bronze. 'It's both surprising and impressive that AI systems can now solve IMO-level problems. However, the exact methods these AI systems use to arrive at their solutions remain somewhat unclear,' Kanav Talwar told The Indian Express. Talwar is the only member of the Indian contingent who outperformed both AI models, scoring two points higher than them. 'This is not unexpected. AI systems work on large amounts of training data, so if they are fed enough Olympiad-level problems and their solutions, the AI system can memorise patterns (e.g., spotting cyclic quadrilaterals in geometry) for solving certain scenarios,' Aarav Gupta, another gold medal-winner, said. What's behind the rivalry between OpenAI and Google DeepMind? This year was the first time IOM organisers officially worked with tech companies to allow their AI models to take part in the competition. While Google was part of this inaugural cohort, OpenAI wasn't. The final scores achieved by the AI models were certified by IMO judges, and companies were reportedly asked to wait a few months before publishing the results in order not to steal the spotlight from the human medal-winners. However, OpenAI was the first to go public with the results. The Microsoft-backed AI startup on Saturday, July 19, announced that its unreleased AI model had achieved a gold medal-worthy score, but the results have not been certified by IMO judges. Instead, OpenAI relied on third-party, former IMO medallists to verify and grade the AI-generated solutions. Google, on the other hand, used a general-purpose model called Gemini Deep Think at the competition. The experimental model has 'an enhanced reasoning mode for complex problems that incorporates some of our latest research techniques, including parallel thinking. This setup enables the model to simultaneously explore and combine multiple possible solutions before giving a final answer, rather than pursuing a single, linear chain of thought,' Google said. Gemini Deep Think's results have been officially certified by the IMO. 'We can confirm that Google DeepMind has reached the much-desired milestone […] Their solutions were astonishing in many respects. IMO graders found them to be clear, precise and most of them easy to follow,' said Dr Gregor Dolinar, the president of IMO. While Google has said this version of its Deep Think model will be made available to AI Ultra subscribers after testing, OpenAI has said it does not plan to release an AI model with this level of math capability for several months. Why are IMO gold medals a big deal for AI companies? Despite the rivalry between OpenAI and Google DeepMind, both their AI models essentially tied with the same final score. But their performances also underscore how rapidly AI models are evolving. Last year, Google DeepMind announced that its AI tools, AlphaProof and AlphaGeometry, had achieved an IMO score equivalent to a silver medal. But these AI tools were specially fine-tuned for solving math problems. They also relied on human experts to first translate the problems from natural language into formal programming languages such as Lean and vice versa. The computation for the proofs also took significantly more time. 'This year, our advanced Gemini model operated end-to-end in natural language, producing rigorous mathematical proofs directly from the official problem descriptions – all within the 4.5-hour competition time limit,' Google said. Researchers behind OpenAI and Google's IMO efforts this year also claimed that the gold-medal results showed how far AI reasoning models have come in solving problems that cannot be easily checked or verified. While AI models may be approaching elite human mathematical reasoning, India's math talents believe that they still cannot match the emotion and creativity involved. 'IMO participants not only solve problems but also experience the unique emotions, excitement, and mental challenge that come with the exam environment which is what makes the IMO truly special,' Talwar said. Archit Manas also agreed that AI models could probably find it hard to solve mathematical problems that require truly new ideas. 'For example, an AI model trained on pre-IMO 2007 ideas would find it hard to solve IMO 2007/6,' he told The Indian Express. Where could mathematical AI models be used? The achievements of AI models at this year's IMO suggest that it could be used to crack unsolved research problems in fields like cryptography and space exploration. But LLMs are also prone to stumbling on simple questions like whether 9.11 is bigger than 9.9. Hence, they are said to possess 'jagged intelligence' which is a term coined by Andrej Karpathy, a founding member of OpenAI. 'AI can help mathematicians solve problems and take care of the more mundane computational elements in their work,' Talwar said. 'Maybe AI can be used for checking proofs and even for brainstorming, but in my opinion, AI being able to replace mathematicians is a long way off,' Gupta opined. When asked if they would recommend using AI tools to train for future Olympiads, Talwar said, 'Maybe in the future, AI can help in math Olympiad preparation in a way that is analogous to chess, where the AI could suggest better ideas on specific problems.'
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First Post
11 minutes ago
- First Post
We are not what you think: How Greece made a case for diaspora to return
Roughly 600,000 Greeks, mostly young, skilled and university-educated, left the country between 2010 and 2021 due to the economic meltdown. Athens is now making effort to reverse the brain drain read more Greece is reaching out to its skilled expats scattered across Europe, urging them to come back home as part of a broader effort to reverse the brain drain sparked by the 2010 debt crisis. Even with challenges like low pay and limited career opportunities, there are signs that some are considering a return. Labour minister tours Europe Labour Minister Niki Kerameus is leading the charge, hitting the road in cities like London and Amsterdam alongside Greek employers to persuade young professionals that Greece has transformed. 'People often see us as the representatives of the state that drove them away,' she was quoted as saying by the Financial Times. 'The biggest challenge is proving that today's Greece has nothing to do with the Greece of 2010 or 2012,' the minister said. STORY CONTINUES BELOW THIS AD Brain drain Roughly 600,000 Greeks, mostly young, skilled and university-educated, left the country between 2010 and 2021 due to the economic meltdown, leaving behind a shrinking workforce and a shortage of skilled professionals. Surveys from BrainRegain highlight low wages, scarce job prospects, and distrust in the system as major hurdles for those thinking of returning. Still, 2023 marked a turning point: for the first time since 2009, more people returned to Greece than left. Eurobank's Chief Economist Tassos Anastasatos noted that 60 per cent of these returnees were aged 20 to 44, a key group for the job market. Government offers incentive To sweeten the deal, the government is offering perks like a 50 per cent income tax cut for seven years, which has helped about 6,000 people since 2020. But officials stress that money alone won't cut it—changing how people view Greece is just as crucial. The 'roadshow' kicked off in 2024 and will hit New York later this year. Companies like Aegean Airlines, Piraeus Port Authority, Deloitte, and Lidl are on board, some even offering jobs on the spot. Challenges Despite a 28 per cent rise in average wages since 2016, most professionals earning over €1,600 a month are barely keeping up with inflation. Bank of Greece advisor Dimitris Malliaropulos put it bluntly: 'There can be no growth without human capital,' stressing the need for better pay and ongoing education policies. One returnee, Avgousta Stanitsa, an architect and AI researcher, moved back to Athens from the UK while five months pregnant. She landed a job at EY through a government career fair. 'The fact that my pregnancy wasn't seen as a barrier really impressed me,' she said, noting a shift in workplace attitudes toward motherhood and work-life balance. While Greek salaries don't match UK levels, Stanitsa said the tax breaks help her maintain a decent quality of life.
Economic Times
15 minutes ago
- Economic Times
Siri-ously? AI Got Clever, Not Conscious
By 2025, artificial intelligence will be an influential social force, not just a technological trend. AI systems have composed code, authored legislation, diagnosed medical conditions, and even composed music. But it became clear that despite the fact that machines got better at speed, cleverness, and oddly creative powers, they were lacking one essential element of intelligence: common sense, empathy, and humanity. Technically, 2025 saw many breakthroughs. OpenAI's GPT-4.5 and Anthropic's Claude 3.5 became popular choices for solving complex problems in business. Google DeepMind's Gemini amazed researchers with its strong reasoning skills. Meta's open-source Llama 3 models made cutting-edge tools available to more people. AI agents like Devin and Rabbit R1 were introduced to handle tasks ranging from personal chores to business processes. Yet, beyond such revolutions, a grim reality set in: AI still does not really get us. Meanwhile, generative models flirted with creativity but faltered with ethics. Deepfakes, which were previously easy to detect, were now nearly impossible to distinguish from actual videos and created confusion during political campaigns in various nations. Governments scrambled to codify the origins of content, whereas firms such as Adobe and OpenAI inserted cryptographic watermarks, which were hacked or disregarded shortly struggled most with social and emotional knowledge. Even with advances in multimodal learning and feedback, AI agents were unable to mimic true empathy. This was especially evident in healthcare and education, where communications centered on the human. Patients were not eager to trust the diagnoses from emotionless avatars, and students were more nervous when interacting with robotic tutors that weren't year wasn't filled with alarm bells. Open sourcing low-barrier models initiated a surge in bottom-up innovation, particularly in the Global South, where AI facilitated solutions in agriculture, education, and infrastructure. India's Bhashini project, based on local-language AI, became a template for inclusive tech development. One thing is certain in 2025: AI is fantastic but fragile. It cannot deal well with deeper meaning, but it can convincingly simulate intelligence. While not intelligent enough to guide us, machines are now intelligent enough to astonish us. While at present humans enjoy the advantage, the gap is closing faster than we was less about machines outsmarting humans than about redefining what intelligence is. AI showed limits in judgment, compassion, and moral awareness, even as it exhibited speed, scope, and intricacy. These are not flaws; they are reminders that context is as vital to intelligence as computation. The actual innovation is not in choosing between machines and humans but in creating a partnership in which the two complement each other's strengths. Real advancement starts there.
