Latest news with #GPT-5
Time of India
10 hours ago
- Science
- Time of India
How to Become an AI Genius: Lessons students can learn from Meta's $100 million hires
If you want to become an AI genius – the kind that Mark Zuckerberg offers $50–$100 million to join his quest for artificial general intelligence (AGI) – here's the blueprint, decoded from Meta's elite hires. 1. Build a rock-solid maths foundation Almost every AI superstar Meta poached – from Lucas Beyer to Trapit Bansal – started with hardcore mathematics or computer science degrees. Linear algebra, calculus, probability, and optimisation aren't optional. They are your bread and butter. Why? Because AI models are just giant stacks of matrix multiplications optimised over billions of parameters. If you can't handle eigenvectors or gradient descent, you'll be stuck fine-tuning open-source models instead of inventing the next GPT-5. 2. Specialise in deep learning Next comes deep learning mastery. Study neural networks, convolutional networks for vision, transformers for language, and recurrent models for sequence data. The Vision Transformer (ViT) co-created by Lucas Beyer and Alexander Kolesnikov redefined computer vision precisely because they understood both transformer architectures and vision systems deeply. Recommended learning path: Undergraduate/early coursework : Machine learning, statistics, data structures, algorithms. Graduate-level depth : Neural network architectures, representation learning, reinforcement learning. 3. Research, research, research The real differentiator isn't coding ability alone. It's original research. Look at Meta's dream team: Jack Rae did a PhD in neural memory and reasoning. Xiaohua Zhai published groundbreaking papers on large-scale vision transformers. Trapit Bansal earned his PhD in meta-learning and reinforcement learning at UMass Amherst before co-creating OpenAI's o-series reasoning models. Top AI labs hire researchers who push knowledge forward, not just engineers who implement existing algorithms. This means: Reading papers daily (Arxiv sanity or Twitter AI circles help). Writing papers for conferences like NeurIPS, ICML, CVPR, ACL. 4. Dive into multimodal and reasoning systems If you want to be at the AGI frontier, focus on multimodal AI (vision + language + speech) and reasoning/planning systems. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Glicemia acima de 100? Insira essa fruta na sua dieta Saúde Nacional Undo Why? Because AGI isn't just about language models completing your sentences. It's about: Understanding images, videos, and speech seamlessly Performing logical reasoning and planning over long contexts For example, Hongyu Ren's work combines knowledge graphs with LLMs to improve question answering. Jack Rae focuses on LLM memory and chain-of-thought reasoning. This is the cutting edge. 5. Optimise your engineering skills Finally, remember that AI breakthroughs don't live in papers alone. They need to run efficiently at scale. Pei Sun and Joel Pobar are prime examples: engineering leaders who ensure giant models run on hardware without melting the data centre. Learn: Distributed training frameworks (PyTorch, TensorFlow) Systems optimisation (CUDA, GPUs, AI accelerators) Software engineering best practices for scalable deployment The bottom line Becoming an AI genius isn't about quick YouTube tutorials. It's about mastering mathematics, deep learning architectures, original research, multimodal reasoning, and scalable engineering. Do this, and maybe one day, Mark Zuckerberg will knock on your door offering you a $50 million signing bonus to build his artificial god. Until then, back to those linear algebra problem sets. The future belongs to those who understand tensors. Is your child ready for the careers of tomorrow? Enroll now and take advantage of our early bird offer! Spaces are limited.
India Today
16 hours ago
- India Today
Sam Altman has a word of advise for ChatGPT users: You should not trust it blindly, here is why
Sam Altman, CEO of OpenAI, has urged users of ChatGPT not to place blind trust in the popular AI chatbot, warning that the technology, while powerful, is far from perfect. Speaking on the first episode of OpenAI's official podcast, Altman acknowledged the surprising level of faith users place in ChatGPT, despite its well-known limitations. 'People have a very high degree of trust in ChatGPT, which is interesting, because AI hallucinates,' he said. 'It should be the tech that you don't trust that much.'advertisementThe comment has sparked debate in tech circles and among everyday users, many of whom rely on ChatGPT for help with writing, research, parenting advice and much more. But Altman's message was clear: ChatGPT, like all large language models, can make convincing but false or misleading claims -- and should be used with works by predicting the next word in a sentence based on patterns in the data it has been trained on. It doesn't understand the world in a human sense and occasionally produces inaccurate or entirely made-up information. In the AI world, this is referred to as 'hallucination'. Altman stressed the importance of transparency and managing user expectations. 'It's not super reliable,' he said. 'We need to be honest about that.'Despite these flaws, the chatbot is widely used by millions of people each day. Altman acknowledged this popularity but pointed out the potential risks of overreliance, especially when users take its answers at face also addressed some of the new features coming to ChatGPT, including persistent memory and the possibility of ad-supported models. While these developments aim to improve personalisation and monetisation, they have raised fresh concerns about privacy and data comments also echo ongoing debates within the AI community. Geoffrey Hinton, often called the 'godfather of AI', has also weighed in. In a recent interview with CBS, Hinton revealed that despite having warned about the dangers of superintelligent AI, he himself tends to trust GPT-4 more than he probably should.'I tend to believe what it says, even though I should probably be suspicious,' Hinton demonstrate the model's limitations, he tested GPT-4 with a simple riddle: 'Sally has three brothers. Each of her brothers has two sisters. How many sisters does Sally have?' GPT-4 answered incorrectly. The right answer is one—Sally herself. 'It surprises me it still screws up on that,' Hinton said, before adding that he believes future models, such as GPT-5, may get it Altman and Hinton agree that AI can be incredibly useful but should not be mistaken for a flawless source of truth. As AI becomes more embedded in daily life, these warnings serve as an important reminder: trust, but verify.- Ends
Hans India
16 hours ago
- Hans India
Sam Altman Urges Caution: Don't Blindly Trust ChatGPT, Verify Its Answers
Sam Altman, the CEO of OpenAI, has issued a clear warning to users of ChatGPT—do not trust the AI chatbot without question. Speaking on the debut episode of OpenAI's official podcast, Altman acknowledged the surprising level of trust people place in the tool, despite its known limitations. 'People have a very high degree of trust in ChatGPT, which is interesting, because AI hallucinates,' Altman noted. 'It should be the tech that you don't trust that much.' His candid remarks have sparked fresh discussions in the tech world and among regular users, many of whom depend on ChatGPT for everything from writing and research to personal advice. Altman emphasized that, while powerful, the chatbot is prone to generating inaccurate or fabricated responses—a phenomenon widely referred to in the AI field as 'hallucination.' ChatGPT functions by predicting the next word in a sequence based on patterns learned during training. However, it lacks real-world understanding and occasionally outputs misleading or incorrect information. 'It's not super reliable,' Altman said. 'We need to be honest about that.' Despite these flaws, ChatGPT continues to be a go-to tool for millions daily. Altman acknowledged its popularity but warned of the potential risks of overreliance, especially when users accept its answers without scrutiny. The conversation also touched on upcoming features like persistent memory and potential ad-supported models—innovations aimed at personalization and monetization but accompanied by renewed concerns about privacy and data usage. Altman's cautionary stance echoes that of Geoffrey Hinton, often called the 'godfather of AI.' In a recent interview with CBS, Hinton confessed, 'I tend to believe what it says, even though I should probably be suspicious.' To illustrate the model's shortcomings, Hinton tested GPT-4 with a basic riddle: 'Sally has three brothers. Each of her brothers has two sisters. How many sisters does Sally have?' GPT-4 got it wrong. The correct answer is one—Sally herself. 'It surprises me it still screws up on that,' Hinton commented, adding that future models like GPT-5 may offer improvements. Both Altman and Hinton agree on the tremendous utility of AI tools—but they also urge users to approach them with critical thinking. Their message is simple yet crucial: Use AI wisely—trust, but always verify.
Indian Express
19-06-2025
- Business
- Indian Express
‘GPT-5 is arriving this summer': Sam Altman reveals OpenAI's roadmap
Sam Altman seems to be giving interviews one after the other. On Thursday, June 19, the CEO of OpenAI appeared on the company's podcast featuring an extended conversation with host Andrew Mayne. In the pilot episode, which lasted for about 40 minutes, Altman laid out a roadmap focused on offering a unified experience with the release of GPT-5, which is slated for this summer. When it comes to GPT-5, OpenAI seems to be working on a solution to unify its array of model offerings. Based on Altman's interaction, the AI powerhouse is working towards fixing the company's confusing product line-up with GPT-5. Reportedly, the latest generation of GPT will be essentially a simplification of ChatGPT's diverse models into one streamlined user interface. Talking about OpenAI's next frontier AI model, Altman said that it will probably arrive this summer. The CEO also admitted that the current state of the model choice is a 'whole mess'. He stated that the goal is to get back to a simple progression (GPT-5, GPT-6) and do away with the complex variants inferring to models, that is, GPT-4, GPT-4o, etc. Altman explained that the future goal is to develop a unified model that can handle everything seamlessly, from instant questions to complex, multi-step tasks using reasoning and agent-like tools such as Deep Research. This would essentially eliminate the need for switching modes within the ChatGPT interface. Altman also said that there is an internal debate going on over the naming strategy for the upcoming model to convey clarity. He even briefly mentioned Elon Musk, and how the SpaceX chief tried using his influence in the government to unfairly compete. Altman said that a shift towards delivering a unified user experience was taking place because AI has evolved from being a bot that gives instant answers. He said that he is surprised to find that for hard problems, users are willing to wait for a 'great answer'. According to him, this insight is driving the development of more thoughtful reasoning models that could perform like a human expert, essentially taking its own time before answering. This is Altman's second podcast interview this week. On the Uncapped podcast that was uploaded to YouTube on June 17, Altman said that Meta offered his employees $100 million bonuses to recruit them as a part of the social media giant's recent efforts to ramp up its AI strategy.
Phone Arena
12-06-2025
- Business
- Phone Arena
'Something unexpected': OpenAI delays open-weights model, teases surprise twist
OpenAI's CEO has now teased that something very interesting may be coming that's going to be worth the delay of the company's open-weights model. OpenAI has quite a history when it comes to deadlines. There have been delays, changes, and what have you, and now, we're facing another extended timeline. But it may be for good. Sam Altman, OpenAI CEO, announced in a post on X that the company's open-weights model release will be delayed. He says to expect a summer release nonetheless, but not one in June. Curiously, he also mentions their team did "something unexpected" and he hints the wait will be worth it, without revealing other details. OpenAI has been teasing its new open-weights model for quite some time now, and initially, it was planned for an early summer release. This new model would have reasoning capabilities similar to OpenAI's o-series, but open to the public. we are going to take a little more time with our open-weights model, i.e. expect it later this summer but not june. our research team did something unexpected and quite amazing and we think it will be very very worth the wait, but needs a bit longer. — Sam Altman (@sama) June 10, 2025 Open-weights AI models are usually models where the trained parameters are publicly available. This pretty much means that any individual or company can download these fully-trained AI systems and use them for their own projects. This removes the need for training or building a model by each company. Altman isn't specifically saying why the model is being delayed, but something unexpected seems to be stopping the release, and in a good sense. Meanwhile, the entire tech industry is in love with AI and the market is getting more and more competitive as we speak. Including the open-weights market. OpenAI has rivals in the face of Mistral, which released its first range of AI reasoning models, and Deepseek, Microsoft, and Google. All these are also deep into the open-weights AI market. In the meantime, many are waiting on GPT-5, which is the latest update to ChatGPT. There's no official release date announced for the update, but many analysts believe it should launch in the next couple of months, probably in July. Originally, it was expected in May, but obviously, this didn't happen. And it doesn't look likely to launch in June either (we're almost halfway through the month).
