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Google का Free AI Pro Plan Students के लिए Gemini 2.5 Pro, 2TB Storage, और ज़बरदस्त Features! Limited Offer

Google का Free AI Pro Plan Students के लिए Gemini 2.5 Pro, 2TB Storage, और ज़बरदस्त Features! Limited Offer

Time of India4 days ago
मोहिनी केडिया
Produced by: • मोहिनी केडिया
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Navbharat Times• 16 Jul 2025, 9:02 pm
Google का Free AI Pro Plan Students के लिए Gemini 2.5 Pro, 2TB Storage, और ज़बरदस्त Features! Limited Offer
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Elon Musk to launch child-friendly 'Baby Grok' after his ‘social media is bad' warning to kids; netizens ask is it free?
Elon Musk to launch child-friendly 'Baby Grok' after his ‘social media is bad' warning to kids; netizens ask is it free?

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Elon Musk to launch child-friendly 'Baby Grok' after his ‘social media is bad' warning to kids; netizens ask is it free?

Elon Musk on Sunday, July 20, announced that his artificial intelligence startup (xAI) will develop a child-focussed app called 'Baby Grok'. This comes after his earlier warning to kids stating that the social media is bad for them. 'We're going to make Baby Grok @xAI, an app dedicated to kid-friendly content,' he posted on X. He said it's 'inspired by Baby Groot', a character found in American comic books published by Marvel Comics. He didn't disclose other details though regarding this. Musk on May 23 last year said, 'A lot of social media is bad for kids, as there is extreme competition between social media AIs to maximize dopamine!' He had urged 'parents to limit the amount of social media that children can see because they're being programmed by a dopamine-maximizing AI'. Internet users are divided on his new move as some say it's a great idea, whereas others state that children should stay away from screens. One of the users said, 'That's a really good idea.' Another remarked, 'Maybe you should focus on getting the kids away from screens' 'Awesome idea. Would be great for educational purposes,' remarked a third. One of them asked Musk, 'Can you make an educational version and make it for people who want to homeschool their children?' A user reacted, 'Why do you want children on the internet?' Some told him, 'We love you Elon but 'kid-friendly content' is not on the internet. It's reading books and playing outside.' One asked, 'Free for children?' Prior to his announcement, Google had stated that it was developing a dedicated Gemini app for children, aimed at assisting them with homework, answering questions, and helping them create stories. Additionally, parents will have control over their children's access to Gemini through the Family Link app, which allows them to disable the feature if desired. Meanwhile, xAI introduced its latest chatbot, Grok 4, earlier this month, just a few months after the previous version, emphasising the breakneck pace of AI innovation. The launch came shortly after the bot made several antisemitic statements on X, which were met with widespread backlash.

What is Baby Grok? Elon Musk announces kid-friendly AI app after controvery over sexualized AI avatar
What is Baby Grok? Elon Musk announces kid-friendly AI app after controvery over sexualized AI avatar

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What is Baby Grok? Elon Musk announces kid-friendly AI app after controvery over sexualized AI avatar

Elon Musk has announced a new Grok app that xAI is creating to cater to kid-friendly content. The move comes after the billionaire faced criticism for Grok's sexualised AI avatars, which were said to have a negative effect on children. In a post on X, Musk 'We're going to make Baby Grok @xAI, an app dedicate to kid-friendly content' Beyond this, Musk did not disclose details on how the children-focused AI app will differ from xAI's usual offering. Before xAI's announcement, Google had revealed it is working on a special Gemini app for children, designed to help them with homework, answer questions, and create stories. Parents will also have the ability to disable Gemini access for their kids via the Family Link app. Google has clarified there will be no ads or data collection from the kids' version of Gemini, with a focus solely on learning and creative expression. The Grok app recently introduced a new AI avatar called Ani, a blonde anime character resembling a young woman in an off-shoulder black dress with a corset, fishnet tights, and a lacy choker. The character responds to user prompts in a slow, sultry voice, further cementing its profile as an adult AI companion. Many users on social media complained that Ani could encourage dangerous behaviour among minors by providing access to explicit and sexualised content. While the avatar does not use overtly explicit language, it has been reported to disrobe in response to conversations. The biggest concern was that Ani reportedly performed these actions even when the Grok app's Kids Mode was enabled. Earlier this month, xAI also launched the latest version of its language model, Grok 4, which quickly found itself at the centre of controversy after the chatbot began posting anti-Semitic sentiments online and portraying itself as 'Mecha Hitler.' xAI later apologised for Grok's responses, blaming deprecated code and the extremist views of X users for the incident. A few days later, Grok was again in the spotlight after it was revealed that the chatbot had started answering political questions in line with Elon Musk's views, raising concerns that the bot had been adjusted to reflect its master's political ideology.

The quantum inflection point: AI's next leap demands a computing revolution
The quantum inflection point: AI's next leap demands a computing revolution

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The quantum inflection point: AI's next leap demands a computing revolution

We stand at a technological crossroads remarkably similar to the early 2000s, when the internet's explosive growth outpaced existing infrastructure capabilities. Just as dial-up connections couldn't support the emerging digital economy, today's classical computing systems are hitting fundamental limits that will constrain AI's continued evolution. The solution lies in quantum computing - and the next five to six years will determine whether we successfully navigate this crucial transition. The computational ceiling blocking AI advancement Current AI systems face insurmountable mathematical barriers that mirror the bandwidth bottlenecks of early internet infrastructure. Training large language models like GPT-3 consumes 1,300 megawatt-hours of electricity, while classical optimization problems require exponentially increasing computational resources. Google's recent demonstration starkly illustrates this divide: their Willow quantum processor completed calculations in five minutes that would take classical supercomputers 10 septillion years - while consuming 30,000 times less energy. The parallels to early 2000s telecommunications are striking. Then, streaming video, cloud computing, and e-commerce demanded faster data speeds that existing infrastructure couldn't provide. Today, AI applications like real-time molecular simulation, financial risk optimization, and large-scale pattern recognition are pushing against the physical limits of classical computing architectures. Just as the internet required fiber optic cables and broadband infrastructure, AI's next phase demands quantum computational capabilities. Breakthrough momentum accelerating toward mainstream adoption The quantum computing landscape has undergone transformative changes in 2024-2025 that signal mainstream viability. Google's Willow chip achieved below-threshold error correction - a critical milestone where quantum systems become more accurate as they scale up. IBM's roadmap targets 200 logical qubits by 2029, while Microsoft's topological qubit breakthrough promises inherent error resistance. These aren't incremental improvements; they represent fundamental advances that make practical quantum-AI systems feasible. Industry investments reflect this transition from research to commercial reality. Quantum startups raised $2 billion in 2024, representing a 138 per cent increase from the previous year. Major corporations are backing this confidence with substantial commitments: IBM's $30 billion quantum R&D investment, Microsoft's quantum-ready initiative for 2025, and Google's $5 million quantum applications prize. The market consensus projects quantum computing revenue will exceed $1 billion in 2025 and reach $28-72 billion by 2035. Expert consensus on the five-year transformation window Leading quantum computing experts across multiple organizations align on a remarkably consistent timeline. IBM's CEO predicts quantum advantage demonstrations by 2026, while Google targets useful quantum computers by 2029. Quantinuum's roadmap promises universal fault-tolerant quantum computing by 2030. IonQ projects commercial quantum advantages in machine learning by 2027. This convergence suggests the 2025-2030 period will be as pivotal for quantum computing as 1995-2000 was for internet adoption. The technical indicators support these projections. Current quantum systems achieve 99.9 per cent gate fidelity - crossing the threshold for practical applications. Multiple companies have demonstrated quantum advantages in specific domains: JPMorgan and Amazon reduced portfolio optimization problems by 80 per cent, while quantum-enhanced traffic optimization decreased Beijing congestion by 20 per cent. These proof-of-concept successes mirror the early internet's transformative applications before widespread adoption. Real-world quantum-AI applications emerging across industries The most compelling evidence comes from actual deployments showing measurable improvements. Cleveland Clinic and IBM launched a dedicated healthcare quantum computer for protein interaction modeling in cancer research. Pfizer partnered with IBM for quantum molecular modeling in drug discovery. DHL optimized international shipping routes using quantum algorithms, reducing delivery times by 20 per cent. These applications demonstrate quantum computing's unique ability to solve problems that scale exponentially with classical approaches. Quantum systems process multiple possibilities simultaneously through superposition, enabling breakthrough capabilities in optimization, simulation, and machine learning that classical computers cannot replicate efficiently. The energy efficiency advantages are equally dramatic - quantum systems achieve 3-4 orders of magnitude better energy consumption for specific computational tasks. The security imperative driving quantum adoption Beyond performance advantages, quantum computing addresses critical security challenges that will force rapid adoption. Current encryption methods protecting AI systems will become vulnerable to quantum attacks within this decade. The US government has mandated federal agencies transition to quantum-safe cryptography, while NIST released new post-quantum encryption standards in 2024. Organizations face a 'harvest now, decrypt later' threat where adversaries collect encrypted data today for future quantum decryption. This security imperative creates unavoidable pressure for quantum adoption. Satellite-based quantum communication networks are already operational, with China's quantum network spanning 12,000 kilometers and similar projects launching globally. The intersection of quantum security and AI protection will drive widespread infrastructure upgrades in the coming years. Preparing for the quantum era transformation The evidence overwhelmingly suggests we're approaching a technological inflection point where quantum computing transitions from experimental curiosity to essential infrastructure. Just as businesses that failed to adapt to internet connectivity fell behind in the early 2000s, organizations that ignore quantum computing risk losing competitive advantage in the AI-driven economy. The quantum revolution isn't coming- it's here. The next five to six years will determine which organizations successfully navigate this transition and which turn into casualties of technological change. AI systems must re-engineer themselves to leverage quantum capabilities, requiring new algorithms, architectures, and approaches that blend quantum and classical computing. This represents more than incremental improvement; it's a fundamental paradigm shift that will reshape how we approach computation, security, and artificial intelligence. The question isn't whether quantum computing will transform AI - it's whether we'll be ready for the transformation. (Krishna Kumar is a technology explorer & strategist based in Austin, Texas in the US. Rakshitha Reddy is AI developer based in Atlanta, US)

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