Latest news with #A100
Time of India
23-05-2025
- Business
- Time of India
IndiaAI Mission GPU tender round 2: All seven shortlisted bidders clear technical round
All the seven shortlisted companies have qualified in the technical round of IndiaAI Mission's second round of graphics processing units (GPU) tender and their commercial bids were opened on Thursday afternoon, ET has L1 (lowest) price for the various GPU models offered by the bidders and the names of the L1 bidders for various GPU variants will be disclosed next week, people aware of the process selected bidders include Netmagic (now NTT Global Data Centres and Cloud Infrastructure division), Cyfuture India, Sify Digital Services, Vensysco Technologies, Locuz Enterprise Solutions, Yotta Data Services, and Ishan Infotech. ET had reported on May 13 that the Centre has received bids proposing to offer a total of 18,000 GPUs in the second round of the IndiaAI GPU tender and that it expects 15,000 GPUs to finally be offered. Cyfuture has proposed to offer 1,184 GPUs, including Nvidia's H100, L40S and A100 GPUs, AMD's MI300 and MI325 GPUs, and Intel's Gaudi 2 and Gaudi 3 GPUs. It has placed purchase orders for the same, people cited above said. Vensysco has proposed to offer 2,300 GPUs: 2,000 Nvidia H100 GPUs, 100 AWS Trainium 1 GPUs, and 200 AWS Inferentia 2 GPUs. Yotta has proposed to offer Nvidia Blackwell B200s. GPU models that NTT-Netmagic, Sify, Locuz and Ishan propose to offer are not known. While Vensysco and Locuz are Amazon Web Services partners , Ishan is an Oracle partner and NTT-Netmagic is a leading Google Cloud partner in India. Under the first round of the GPU tender concluded in February, IndiaAI Mission is offering 14,517 GPUs on subsidised rates to the country's startups, academics and research organisations. ET had reported on April 26 that the Ministry of Electronics and Information Technology ( MeitY ) had assigned artificial intelligence (AI) projects, or workloads, to three companies selected to supply GPUs under the IndiaAI Mission. The government, however, has not named the beneficiaries of the programme. India gave the cabinet approval for the Rs 10,000-crore India AI Mission in March last year, with a target of creating an artificial intelligence (AI) compute infrastructure by procuring over 10,000 GPUs. As part of the mission, the government is also incentivising the development of local language models built by academia and industry with investment capital and other support. The move is aimed at building up India's AI prowess. ET reported on May 16 that the IndiaAI Mission has received 506 foundation AI model proposals across three phases. As part of the first phase of approvals, was selected to initiate the development of an indigenous foundational model. Sarvam will get access to 4,096 Nvidia H100 GPUs for six months from the IndiaAI Mission's common compute cluster to train its model.
Time of India
23-05-2025
- Business
- Time of India
IndiaAI Mission GPU tender round 2: All seven shortlisted bidders clear technical round
All the seven shortlisted companies have qualified in the technical round of IndiaAI Mission's second round of graphics processing units (GPU) tender and their commercial bids were opened on Thursday afternoon, ET has learnt. The L1 (lowest) price for the various GPU models offered by the bidders and the names of the L1 bidders for various GPU variants will be disclosed next week, people aware of the process said. The selected bidders include Netmagic (now NTT Global Data Centres and Cloud Infrastructure division), Cyfuture India, Sify Digital Services, Vensysco Technologies, Locuz Enterprise Solutions, Yotta Data Services, and Ishan Infotech. ET had reported on May 13 that the Centre has received bids proposing to offer a total of 18,000 GPUs in the second round of the IndiaAI GPU tender and that it expects 15,000 GPUs to finally be offered. Cyfuture has proposed to offer 1,184 GPUs, including Nvidia's H100, L40S and A100 GPUs, AMD's MI300 and MI325 GPUs, and Intel's Gaudi 2 and Gaudi 3 GPUs. It has placed purchase orders for the same, people cited above said. Vensysco has proposed to offer 2,300 GPUs: 2,000 Nvidia H100 GPUs, 100 AWS Trainium 1 GPUs, and 200 AWS Inferentia 2 GPUs. Discover the stories of your interest Blockchain 5 Stories Cyber-safety 7 Stories Fintech 9 Stories E-comm 9 Stories ML 8 Stories Edtech 6 Stories Yotta has proposed to offer Nvidia Blackwell B200s. GPU models that NTT-Netmagic, Sify, Locuz and Ishan propose to offer are not known. While Vensysco and Locuz are Amazon Web Services partners , Ishan is an Oracle partner and NTT-Netmagic is a leading Google Cloud partner in India. Under the first round of the GPU tender concluded in February, IndiaAI Mission is offering 14,517 GPUs on subsidised rates to the country's startups, academics and research organisations. ET had reported on April 26 that the Ministry of Electronics and Information Technology ( MeitY ) had assigned artificial intelligence (AI) projects, or workloads, to three companies selected to supply GPUs under the IndiaAI Mission. The government, however, has not named the beneficiaries of the programme. India gave the cabinet approval for the Rs 10,000-crore India AI Mission in March last year, with a target of creating an artificial intelligence (AI) compute infrastructure by procuring over 10,000 GPUs. As part of the mission, the government is also incentivising the development of local language models built by academia and industry with investment capital and other support. The move is aimed at building up India's AI prowess. ET reported on May 16 that the IndiaAI Mission has received 506 foundation AI model proposals across three phases. As part of the first phase of approvals, was selected to initiate the development of an indigenous foundational model. Sarvam will get access to 4,096 Nvidia H100 GPUs for six months from the IndiaAI Mission's common compute cluster to train its model.
Time of India
20-05-2025
- Business
- Time of India
China's progress in AI cannot be limited and should not be underestimated, says Nvidia CEO Jensen Huang
Live Events Amid escalating technological rivalry between the United States and China, Nvidia CEO Jensen Huang underscored China's growing influence in artificial intelligence (AI), describing its progress as undeniable and an interview with web portal Stratechery, Huang said the rapid rise of Chinese AI companies such as DeepSeek is impressive."China's doing fantastic; 50% of the world's AI researchers are Chinese and you're not going to hold them back, you're not going to stop them from advancing AI. Let's face it, DeepSeek is deeply excellent work," he was in reference to export controls the US has implemented on advanced chips (such as Nvidia's A100/H100) to prevent uncontrolled AI diffusion to China and other simple terms, AI diffusion refers to efforts to slow or control the spread of advanced AI technologies (especially foundational models and compute infrastructure) to geopolitical said the idea to not have America compete in the Chinese market, where 50% of the developers are, makes no sense from a computing infrastructure and computing architectural perspective. "We ought to go and give American companies the opportunity to compete in China," he warned that if US companies don't compete in China, it will in turn allow the Chinese to build a rich ecosystem and new platforms, which would not be this month, Nvidia announced partnerships in the Gulf region , notably with Saudi Arabia and Qatar, to advance AI infrastructure and capabilities. Huang said those countries have an "extraordinary opportunity"."They have an abundance of energy and a shortage of labour, and the potential of their countries is limited by the amount of labour that they have, the amount of people that they have," he said.
Mint
19-05-2025
- Business
- Mint
Pocket FM is training its AI model to scale storytelling. Is the investment worth it?
Audio series startup Pocket FM plans to have a large language model (LLM) up and running by the end of the year. The company has already labelled and categorized its proprietary datasets and is currently testing an early version of its model. 'We're currently testing a very raw model, that is going to take some time. We're also working on getting graphic processing units," said Pocket FM co-founder and chief technology officer Prateek Dixit told Mint. Teams at the company are already working on reinforcement learning for the LLM. Pocket FM expects the LLM to be ready five to six months after that. The startup plans to buy between 30 and 50 of Nvidia's A100 or H100 GPUs in a staggered manner. These units cost anywhere between $8,000 and $25,000 each. Despite the steep costs, Dixit views the investment as strategic. 'It's not just a cost decision, you've to understand. It's more of a strategic asset for how we scale storytelling with AI," Dixit added. Beyond hardware, the LLM push includes infrastructure upgrades, hiring skilled AI engineers, and increased R&D investment. Pocket FM currently spends 8-13% of its revenue (approximately $26 million) on R&D, with 40% of that allocated to AI initiatives. This is expected to go up by 1% to 2%. Pocket FM plans to build their model on top of an open-source foundation model like Meta's Llama 3, tailored specifically for storytelling. The company currently uses open-source models, fine-tuned for its genre-specific needs, but over time, it reached a point where the quality of the content plateaued. 'With our own model training, we can have a step jump in quality," Dixit said. Popular genres of content on the platform include drama, fantasy and thrillers. The company's writers have produced thousands of stories in these categories. The plan is to use the LLM for everything ranging from story creation and comic creation to developing stories, character arcs and even AI-based videos. 'The idea is to take these foundation models and fine-tune them for different writing styles. That is the use case for comics as well," said Dixit. Earlier this year, Pocket FM launched Pocket Toons, its webcomic platform. For this, the company created an AI-powered studio it calls Blaze to produce comics, '20x faster at one-third the cost, automating processes like background rendering, scene composition, and colouring while preserving artistic creativity," the company had said. Pocket FM has been using natural language processing (NLP), a subset of artificial intelligence (AI), for translating across the 10 languages for which it produces audio content. Other use cases include text summarisation, metadata generation and genre tagging. 'An LLM forms the backbone of a powerful IP engine that not only drives our audio formats today but will also power future innovations across multiple storytelling mediums," said Dixit. Is the investment worth it? Experts are divided on whether building a domain-specific language model (DSLM) is worth the cost and can help in the long run. It's hard to say whether a DSLM can stand the test of time, given how fast the AI industry is moving. 'I don't think building a proprietary model is a good idea where the rate of innovation is so fast in the industry," said Anushree Verma, senior director analyst at Gartner. According to Gartner, enterprise spending on such models is expected to reach $838 million in 2025 and grow to $11.3 billion by 2028. The market is expected to grow at a compound annual growth rate of 233%. Open-source generative AI models are emerging as a viable source for domain-specific models, rapidly closing the performance and reliability gap with proprietary models and offering a cost-effective and flexible alternative for model training and specialization, Verma added. 'Building an LLM isn't automatically a strategic advantage. In many cases, a smaller DSLM can outperform a general-purpose LLM in speed, cost-efficiency, and relevance—especially when fine-tuned on proprietary data," said Manpreet Singh Ahuja, tech, media and telecom sector leader and chief clients and alliances officer at PwC India. 'The question is not 'can we build it?' but 'should we.'" His argument is that LLMs are only worth building when a company has a clearly established reason that current models in the market can't satisfy. If a company is unable to prove that or is not able to monetise the model itself or use it across high-scale products, the return on investment is questionable. 'Long-term value comes not from owning the model alone, but from the unique data, applications, and feedback loops built around it," Ahuja added. However, given that Pocket FM knows the use case it wants to build for, a custom LLM can benefit them, even in the long run. What's more, building one that doesn't require them to lease GPUs for training means they don't need to worry about data security concerns and safeguarding their intellectual property. 'Over time, running your own optimized model, especially using open-source foundations, can slash inference costs by up to 80%," said Sameer Jain, managing director at Primus Partners, a global management consulting firm. Inferencing refers to the process where a trained AI model uses its existing knowledge to make its own conclusions on data its never seen before. Eventually, the company expects that by owning its own GPUs and LLMs, it'll be able to reduce its AI costs significantly. 'The unit cost per generation of content at scale gets reduced. We're not talking about one-time use cases. We want to continuously generate inferences from models," Dixit said, adding that they expect their inferencing cost to drop by 20-30%. Deeper AI push Besides LLM, Pocket FM has a co-pilot that is used internally to create content in German, English, and Hindi. The company is still fine-tuning it to work with other Indic languages like Tamil, Telegu, Kannada, Marathi, and Bengali. 'We'll be making a public launch of this tool in a few months," said Dixit. The company is also building AI agents which can participate in every step of the story creation process, from how intense the beginning of a story should be to where a cliff hanger might be appropriate to add. 'We're building them in such a way that individual modules can act and trigger separately. A story could have a really good cliff hanger but bad pacing. I should be able to ask a model to address these specific queries," said the Pocket FM co-founder. Meanwhile, Pocket FM is considering acquisitions for the first time, and is moving with two strategies in mind: lean AI companies building either LLMs for stories or AI-based voice and video and secondly, companies which have large writer communities. 'We're building an AI entertainment suite so it would be great to get companies that can be baked into our systems," Dixit said. While the company hasn't actively set aside money for inorganic growth, they said they're going to be opportunistic about making acquisitions. Pocket FM is knocking on the doors of global private equity players as it looks to raise another round of money. The company is looking to raise between $100 million and $200 million, this time at a unicorn valuation, according toVCCircle in March. The company last raised money in March 2024 in a $103 million Series-D round that was led by Lightspeed India Partners at a valuation of $750 million. So far, the company has cumulatively raised $197 million across rounds and has the likes of Brand Capital, Tencent, Stepstone Group on its cap table. Pocket FM competitor Kuku FM is also leveraging AI for similar use cases. Kuku FM used AI for the creation of scripts of series on its platform, like 'Secret Billionaire,' 'Women of Prison' and 'Bloodstone Fortune.' Across industries, companies are now opting to build their own models as they look to leverage the vast amounts of user data they've collected over the years. Healthify, the health and wellness startup, built their own small language model that runs on top of LLMs from OpenAI and Anthropic. Ed-tech startup Physicswallah is building smaller models to solve questions pertaining to physics, chemistry, mathematics and biology. Strategy this year While the US has always been Pocket FM's main revenue source, accounting for 70-75% of total revenue, the company expects the European market to take off this year. With the $103 million raised last year, the company expanded into Europe and Latin America. Currently, Pocket FM is available in Germany and the UK, where the company entered just six months ago and claims that the two markets have already contributed to 5% of its revenue. Instead of opting to go live simultaneously across Europe, they're staggering their entry into different nations. They'll go live in France in June, then Italy around October and finally, the Netherlands around January in 2026. Dixit expects Europe to contribute up to 30% in two years. As a result, the company said, their revenue will 'grow multi-fold." India currently contributes 10-15% to Pocket FM's revenue. Pocket FM expects that the revenue percentage contribution will remain the same while 'its absolute revenue is expected to grow significantly, potentially 2–3 times." The company claimed it had surpassed $200 million in terms of revenue in FY25, with an annual recurring revenue of $250 million. In FY24, Pocket FM's revenue stood at ₹261 crore, compared to ₹130 crore in FY23, according to regulatory files accessed by business intelligence platform Tofler. The company trimmed losses to ₹16 crore in FY24 from ₹75 crore in FY23. Founded in 2018 by Rohan Nayak, Prateek Dixit, and Nishanth KS Pocket FM started as a audio series platform. The company has since rebranded itself, changing its name to Pocket Entertainment. It now runs three verticals, Pocket FM, Pocket Novels and Pocket Toons.
New Straits Times
19-05-2025
- Business
- New Straits Times
Silicon Power, Silicon Divide: AMD, Nvidia and strategic shifts from tariffs to Malaysia
Silicon Giants in a Fractured World: AMD, Nvidia The latest income statements of AMD (Q1 FY25) and Nvidia (Q4 FY25) are more than just financial snapshots. They're real-time barometers of a wider geopolitical reordering, one shaped by tariffs, tech wars, and a recalibration of supply chains, in which Malaysia is quietly emerging as a strategic node. Let's begin with the raw numbers. AMD posted Q1 FY25 revenues of US$7.4 billion, up 36 per cent year-on-year, while Nvidia, for Q4 FY25, came in with a staggering US$39.3 billion in revenue, a 12 per cent quarter-on-quarter increase. The contrast is stark, not just in scale but in sectoral drivers. For AMD, data centre revenue rose 57 per cent YoY to US$3.7 billion, while client and gaming segments pulled in US$2.3 billion (+68 per cent) and US$0.6 billion (-30 per cent), respectively. For Nvidia, data centre alone delivered a whopping US$35.6 billion, up 16 per cent QoQ, with gaming contributing US$2.5 billion, relatively flat. Yet these numbers don't just reflect market demand. They map the strategic outcomes of US trade policy. Ever since the Trump administration initiated sweeping tariffs on Chinese imports and targeted Chinese tech giants like Huawei and SMIC with export controls, semiconductor players like AMD and Nvidia have been forced to reconfigure their upstream and downstream supply chains. Nvidia's outsized data centre profits - US$22.1 billion in net profit with a 56 per cent margin - owe much to AI-driven demand, notably from US hyperscalers like Microsoft, Meta, and Amazon. But more importantly, its success reveals how America's restrictions on advanced GPU exports to China have created artificial scarcity. By blocking sales of top-end chips like the A100 and H100 to China, the US has redirected demand inward and toward allied countries. AMD, too, with a more modest net profit of US$0.7 billion (10 per cent margin), is adjusting its chip strategy amid similar geopolitical guardrails. Realignment of the Global Chip Supply Chain That's where Malaysia enters the equation. The country has long been a key back-end player in the global semiconductor value chain, especially in assembly, testing, and packaging (ATP). Post-trade war, it's evolving into a preferred "friend-shoring" hub for US chipmakers looking to diversify away from China without sacrificing efficiency. US-based companies have increasingly leaned on Malaysian facilities in Penang and Kulim, many of which are operated by American subcontractors or joint ventures. The US$40 billion credit guarantee push for SMEs announced by Malaysia's 2025 Budget, for instance, signals a clear intent to scale local participation in the high-tech economy, particularly in electronics manufacturing services (EMS) and chip packaging. This ties directly to the supply chain recalibration by giants like AMD and Nvidia, whose chips might be fabricated in Taiwan or South Korea, but are increasingly tested and packaged in Malaysia before global distribution. Let's tie this back to costs. Nvidia's cost of revenue was US$10.6 billion, with operating expenses at US$4.7 billion, including US$3.7 billion in R&D (nine per cent of revenue), a figure AMD mirrors proportionally, spending US$1.7 billion or 23 per cent of its smaller revenue base. But the geopolitical price is steeper: Nvidia and AMD must not only outspend but also outmaneuver regulatory constraints and navigate the tech bifurcation between the US and China. Trump's tariffs and Biden's CHIPS Act are two sides of the same coin, strategic decoupling dressed in different fiscal garments. The recent export controls on advanced AI chips to China, layered with tighter investment screening by CFIUS and Malaysia's own shift toward national chip policy, signal a new paradigm. Malaysia, through entities like MIDA and with help from US strategic allies, is now marketing itself not just as a passive manufacturing base but as a neutral node in the techno-political chessboard - attractive to US firms wary of overdependence on Taiwan or facing regulatory cliffs in China. Even more crucially, Malaysia's participation in the Johor-Singapore Special Economic Zone and the development of smart logistics, chip clusters, and digital infrastructure form the long game. With US sanctions reshaping semiconductor demand, Malaysia's neutral foreign policy and sound infrastructure are making it a default choice in the East's version of the "Silicon Triangle," next to Vietnam and India. So what do AMD and Nvidia's financials tell us in 2025? More than just profits and margins, they reveal a techno-economic realignment accelerated by tariffs, tempered by innovation, and quietly enabled by strategic nations like Malaysia. In a world where AI, chips, and geopolitics increasingly converge, Malaysia isn't just riding the wave - it's positioning itself to shape the tide. * The writer is a geopolitical and economic analyst. He regularly writes on how global macroeconomic trends intersect with trade and industrial policy.
