Год: 2025

Three former Google and Meta silicon executives have raised $100 million to launch Majestic Labs, a startup developing high-capacity AI servers designed to cut data centre costs for hyperscalers.

Founded by Ofer Shacham, Sha Rabii, and Masumi Reynders, Majestic Labs is building patent-pending silicon architecture that promises up to 1,000 times the memory capacity of conventional enterprise servers. The company says its system can replace up to ten existing server racks, potentially reducing power, cooling, and space requirements for large AI data centers.

Majestic’s $71 million Series A, led by Bow Wave Capital with participation from Lux Capital, closed in September. The company has been quietly operating since late 2023 and now employs fewer than 50 people split between Los Altos, California, and Tel Aviv, Israel. Prototypes are expected in 2027, with pre-orders already under discussion.

“We’re not trying to replace GPUs across the board — we’re solving for memory-intensive AI workloads where the fixed compute-to-memory ratio becomes a constraint,” Shacham, Majestic’s CEO, told CNBC. The startup is targeting hyperscalers and enterprises in data-heavy industries such as finance and pharmaceuticals.

The timing aligns with surging global investment in data centre infrastructure. Tech giants Alphabet, Meta, Microsoft, and Amazon together expect capital expenditures to exceed $380 billion in 2025, much of it driven by AI workloads.

Majestic’s architecture aims to “collapse” multiple racks of hardware into a single server, which the founders say could dramatically increase efficiency. “NVIDIA makes excellent GPUs and has driven incredible AI innovation,” Shacham added, “but our goal is to complement that by solving for memory bottlenecks.”

The trio’s collaboration dates back two decades. Reynders joined Google in 2003 and later became director of product management for silicon. Rabii, who sold his chip design startup Arda Technologies to Google in 201, led the Argos video chip team at YouTube. Shacham, who sold Chip Genesis to Google in 2013, oversaw silicon design for consumer hardware.

In 2018, the three moved to Meta, where they founded the Facebook Agile Silicon Team (FAST). After layoffs at Reality Labs in 2023, they regrouped to start Majestic Labs, focusing on one of AI’s biggest infrastructure bottlenecks — memory.

“We’ve been friends and colleagues for a long time, so this notion of working together and doing something exciting has always been in the periphery,” Reynders said.

The post AI Server Startup Majestic Labs Comes Out of Stealth With $100 Mn Funding appeared first on Analytics India Magazine.

As artificial intelligence and emerging technologies shape the nature of work, industry leaders are urging organisations to rethink how they deploy technology, such that it also empowers people.

“A forward-looking organisation looks at AI and technology more as a collaborator than a threat,” said Surya Prakash Mohapatra, global competency head for industry cloud and digital business at Wipro, at the Bengaluru Skill Summit 2025 held from November 4-6.

This mindset shift is essential as companies navigate roles that are rapidly evolving due to technological intervention.

Mohapatra emphasised that AI’s power lies in its accessibility. In the modern enterprise, AI should not be reserved for specialists, it must be democratised. “There is absolute democratisation of data and AI… everybody has access to AI tools and platforms.” This democratisation pushes organisations to redesign their processes so employees at every level can participate in the value creation AI enables.

But, as AI becomes infused into workflows, the human element becomes even more essential. Mohapatra stressed the importance of “contextualising the human element” because human beings “understand the context… they have empathy… they understand the customers, they understand the stakeholders.”

The Human Intelligence AI Can’t Replace

Shyamala Jhaveri, VP of HR operations and global shared services deployment program lead at Alstom, extended the idea by touching upon the emotional and ethical gaps that algorithms cannot fill. “We are in a world where algorithms drive decisions, strategy is driven by data, and human attention is fragmented,” she observed.

She referenced a popular idea attributed to Microsoft CEO Satya Nadella: “In the future, the most scarce commodity would be human attention”. In a hyper-automated world, attention becomes a differentiator, not a given.

Jhaveri also recounted a case where a logistics company introduced an AI scheduling algorithm that improved delivery metrics but unintentionally harmed trust. The drivers felt they were “working for an algorithm versus with an algorithm” until a leader accompanied them and discovered that the system didn’t factor in “the human chaos, a sick child at home, flood, road blocks, traffic”. Only after incorporating these realities did trust and morale improve.

Lessons from Robotics and Daily Life

While Mohapatra and Jhaveri focused on organisational AI, Dr Basaralu Sudharshan, skilling and education executive advisor for World Alliance for Microcredentials, grounded the conversation in concrete examples of automation.

He described how Finnish vocational institutes use a fully automated robotic milking system managed by a single person, with behavioural intelligence built into its design. Robots even deliver goods autonomously in rural towns, adapting to environmental challenges and interacting with children who get in their way.

These stories highlight how deeply technology has penetrated everyday operations, far beyond corporate boardrooms. But Sudharshan emphasised that the design of such systems must consider human behaviour, especially as automation scales. This requires strong vocational training, micro-credentialing, and skilling systems that respond to the needs of a technology-driven economy.

He also warned that technology alone cannot compensate for missing soft skills. Young professionals, he noted, often lack people skills because of “the technology advancement…the way we have moulded them” has reduced real human interaction. In an AI-enabled world, this becomes a real disadvantage.

AI-Infused Learning Ecosystems

Regional HR director for Asia Pacific, Middle East & Africa regions at Kyndryl, Dr Augustus G S Azariah, brought a complementary perspective focused on how organisations can leverage AI to build continuous learning cultures. He emphasised that companies can integrate AI into their HR and learning systems to make employee skills more visible and actionable. “One of the ways of doing [this] is by using technology, by using AI… and merging it with your pipeline of future skills and work.”

This fosters transparency, eliminating the outdated notion that employee profiles should be confidential and facilitating improved internal mobility. When employees acquire “hot skills,” Azariah recommended rewarding them more to reinforce a performance culture aligned with future business needs.

His message underscored that AI is not only a tool for automation, it is a foundation for talent transformation. The organisations that thrive will be those that use technology to unlock human potential rather than constrain it.

A clear narrative emerged at the summit: the future of work relies on balancing AI’s computational power with human emotional and ethical strengths. This consensus believes that technology enhances human value when organisations intentionally integrate empathy, context, and continuous learning into their systems.

The post The Real Future of Work Blends Algorithms and Humanity, Say Leaders appeared first on Analytics India Magazine.

CAMB.AI and Broadcom have announced a collaboration that embeds CAMB.AI’s generative voice model, MARS, directly into Broadcom’s neural processing unit (NPU) chipsets.

The partnership enables text-to-speech and localisation features to run natively on consumer devices without depending on the cloud.

The integration enables real-time translation, dubbing, captioning, and audio descriptions to function locally, eliminating latency and privacy concerns while reducing costs for users and content providers.

Akshat Prakash, co-founder and CTO of CAMB.AI, said, “By partnering with Broadcom, we can deliver this capability to consumers globally in a way that is faster, more private, and more integrated into everyday devices than ever before.”

Running on Broadcom’s SoC-integrated NPU, CAMB.AI’s text-to-speech model converts written text into natural speech in multiple languages. This approach supports accessibility for visually impaired users, improves communication in e-learning and customer service, and cuts reliance on external servers.

Rich Nelson, SVP and GM of Broadcom’s broadband video group, said, “We are enabling next-generation user experiences that are both highly intelligent and privacy-first.”

The next phase of the collaboration will explore moving CAMB.AI’s real-time translation model to Broadcom’s on-device NPU, enabling translation across more than 150 languages. Broadcom’s chips already power over 500 million devices globally, including set-top boxes and broadband gateways, meaning the new capability could bring multilingual and accessible content to homes worldwide.

CAMB.AI, known for its multilingual AI localisation work with organisations such as IMAX, Comcast NBCUniversal, and Major League Soccer, has built MARS and BOLI models that are already available on AWS Bedrock and Google Vertex AI.

The partnership with Broadcom marks a move towards embedding localisation and accessibility at the hardware level, bringing AI-powered communication closer to users than ever before.

The post CAMB.AI, Broadcom Bring Voice AI Directly to Chip appeared first on Analytics India Magazine.

SoftBank Group recently reported a consolidated net income of ¥3.32 trillion (~$22.1 billion) for the six months ended September 30, up 168% from the previous year, according to its latest financial report.

According to the company’s consolidated financial report, the increase was primarily driven by investment gains from OpenAI and share sales in companies such as NVIDIA and T-Mobile.

The company reported that income before tax increased 152% year-over-year to ¥3.69 trillion, with total investment gains reaching ¥3.93 trillion (~$26.2 billion).

SoftBank confirmed it will invest up to $40 billion in OpenAI through the SoftBank Vision Fund 2 (SVF2), with an effective investment of $30 billion after syndicating $10 billion to co-investors. The first $10 billion closing was completed in April, followed by a planned $30 billion second closing in December this year.

Moreover, SoftBank announced a joint venture, SB OAI Japan, with OpenAI on November 5. This initiative was formed to provide what the company called ‘Crystal intelligence’, which will transform the corporate management and operational practices of Japan’s enterprises through the use of AI.

SoftBank’s earnings reflect CEO Masayoshi Son’s renewed push into AI infrastructure, positioning the group as a key player in global AI development. The company is reinforcing its long-term AI strategy while using its Arm and Vision Fund assets to secure new financing.

AI Bets and Asset Sales

SoftBank continued to monetise assets to fund its investment drive. Between June and October, SoftBank raised roughly $17 billion from selling shares in T-Mobile, Deutsche Telekom and NVIDIA, including the latter’s entire stake worth $5.83 billion.

The company issued domestic and foreign bonds totalling over ¥1 trillion (~$6.67 billion) and secured bridge loans of $15 billion for its OpenAI and Ampere acquisitions.

SoftBank’s results underscore its ongoing shift towards AI-driven investments and high-value asset realignment. With record profits and strategic sales completed, the group appears poised to deepen its technology exposure ahead of 2026.

To support its aggressive investment strategy, the company also expanded its margin loan facility, backed by Arm shares, from $13.5 billion to $20 billion last month, with $11.5 billion still undrawn as of November 11.

SoftBank also announced two major acquisitions aimed at strengthening its AI and semiconductor portfolios.

It entered into an agreement on March 19 to acquire Ampere Computing Holdings LLC, a US-based semiconductor design firm specialising in AI compute on the Arm platform, for $6.5 billion. The approved deal is expected to close by the end of this year, making Ampere a wholly owned subsidiary of the company.

That apart, on October 8, SoftBank signed a definitive agreement with ABB to acquire its robotics business for $5.375 billion. The transaction is expected to close in mid to late 2026, pending regulatory approvals in the US, EU and China.

The ‘AI Bubble’ Enters the Frame

As SoftBank pivots heavily into AI, the broader question of an “AI bubble” has gained traction among investors and industry watchers. Some argue that parallels with the dot-com boom of the late 1990s are emerging, including lofty valuations, heavy capital spending and nascent business models.

During a Bloomberg interview, Jensen Huang, CEO of NVIDIA, rejected the notion that we’re in a bubble.

He mentioned that this was due to a natural transition from an old computing model to accelerated computing. He believes that AI has become “good enough” because of its reasoning, research and thinking capabilities, which are generating tokens that are worth paying for.

“All of these different AI models we’re using, we’re using plenty of services [provided by the models] and paying happily to do it.”

In a recent roundtable discussion with the Financial Times, Huang explained why he believes today’s AI boom differs from the dot-com frenzy of the late 1990s. This referred to a time when investors rushed to pour money into internet startups at the mere mention of the ‘World Wide Web’, inflating valuations far beyond their actual worth. When the bubble burst, most of those companies vanished, leaving only a handful of survivors, like Amazon, to define the next era of tech.

Huang believes the AI boom is not like the dot-com boom because back then, the majority of the fibre was “dark”, meaning unused. Today, nearly “every GPU you can find is lit up and used.”

A Wave of Sell-Offs

On the contrary, Michael Burry, the investor famed for his bet against the US housing market ahead of the 2008 crash, has signalled that the AI-driven surge may be heading for a reckoning.

His hedge-fund firm, Scion Asset Management, disclosed put options on approximately one million shares of NVIDIA (~$187 million) and around five million shares of Palantir Technologies (~$912 million) in the third quarter.

This move led many market watchers to speculate whether the broader AI ecosystem and heavyweights like NVIDIA would be at risk.

Chevy Chase Trust trimmed its NVIDIA stake by 1.3 lakh shares on Tuesday, reducing its holding to 1.6 crore shares, valued at roughly $2.543 billion, and making up about 7.4% of the fund’s portfolio.

Other investors, such as Dale Q Rice Investment Management and Private Trust Co. NA, are also adjusting holdings.

The logic underpinning Burry’s stance appears grounded in valuation fatigue and structural risk. NVIDIA’s dominant role in AI infrastructure, rising capital expenditure on AI platforms, and spiralling valuations have prompted questions.

For investors and firms like SoftBank, which has already sold its entire NVIDIA stake, Burry’s actions add a cautionary voice to what has been an otherwise bullish AI narrative.

The post SoftBank Goes All In on OpenAI, Cashes Out Entire NVIDIA Stake appeared first on Analytics India Magazine.

AI coding tools are making developers dependent on them. Worse, now companies are depending on them, almost forcing developers to use it, and in some cases, even asking them to pay for it. All of this is when the choice should rest with the developers.

On the r/developersIndia subreddit, a post by a young full-stack developer working in an Indian company has struck a chord with hundreds of coders across the country. The developer says his new company has made Cursor mandatory for every engineer.

“They expect features built in a single day,” he wrote. “Even during meetings when I say it’s going to take longer just so I can hand-build it and learn something, they’re like, ‘You have Cursor right, just use that.’”

‘All I Do is Prompt Everyday’

The redditor’s description of the state is very similar to what has been happening in the industry globally. “I thought I was going to learn something here, but all I do is prompt every day. I don’t understand anything that’s going on with the project. I feel like my skills are fading and I hate working here because it feels like I’m one prompt away from either fixing the bug or ruining the app.”

Adithya S Kolavi, founder of CognitiveLabs, agrees that he encourages developers in his company to use AI tools as much as possible, as he believes that not being able to learn coding because of AI is simply wrong. “I started learning more when I started using AI to code,” he told AIM. “There are things that I have already learnt, and in that scenario, I mainly review the code AI has written.”

“I would go as far as to say, if you are not using AI as a coding assistant in this age, it will be hard to catch-up with people who are,” he said, adding that those who have recently started coding would benefit if they avoid using AI tools for every task.

That post now sits among many others from Indian developers describing the same shift: AI-first workplaces where tools like Cursor, Copilot, and Gemini CLI are no longer optional.

Another user, blackpearlinscranton, a backend developer, said their company tracks how often employees use Cursor. “We are warned if Cursor requests are low for more than 3-4 working days,” they wrote. “For the past two months I feel like a bridge who accepted/refined Cursor output and got it merged.”

Many said the shift has killed the joy of problem-solving. “My manager said we can’t code better than AI,” one developer wrote. “It’s been two months and our team is shipping code faster.”

That speed has come at a cost with the quality of the code going down. Even though several developers argue that their productivity has increased several times because of these coding tools, the forced usage of it, raises questions.

Brijesh Patel, founder and CTO of SNDK Corp, earlier told AIM that the answer lies in empowerment, not enforcement. “Developers should be empowered to choose the tools that best align with their work style and the project’s needs,” he said, while adding that no developer in SNDK Corp is forced to use AI tools, but just encouraged to find whatever works best for them.

Push Back?

This comes just days after another viral Reddit post of an Indian developer who said their startup forced employees to pay for Cursor from their own pockets—$20 per month—with promises of reimbursement that never came.

When developers later asked for repayment, the company demanded proof of Cursor usage and test coverage metrics before approving it. “We are being forced to purchase the subscription, use it for company work, and beg for reimbursement,” the post said.

That episode, and now the recent spate of similar posts, point to a new kind of pressure creeping into India’s software workforce. Managers chasing productivity metrics are using AI adoption as a proxy for performance.

Kolavi asserted that companies should sponsor the tools and provide free alternatives as well, instead of asking developers to pay for it. “What matters most is being able to ship useful code as fast as possible. We had a few interns who were trying to write all the code from scratch, which was actually holding others back who were using AI to code,” he said.

Some developers are quietly pushing back. One Bengaluru-based engineer admitted writing a script to send “nonsensical prompts just to exhaust it,” so management would think he was using Cursor. “If your company expects people to blindly trust whatever slop Cursor produces, then you need to jump ship,” wrote a staff engineer.

But not everyone thinks it’s wrong. Several experienced developers believe AI agents are simply the next phase of programming and also recommend it, though not coax people to use it.

The real skill of a software engineer is not writing code but designing what to write. Some cite the cult saying that AI won’t replace a programmer but a developer who knows how to use AI will.

Read: AI is Taking Over Coding at Indian Companies

Neeti Sharma, CEO of TeamLease Digital, said that many developers have created their own versions of GPT, which is nothing wrong as long as the work is getting done. But, respecting an organisation’s governance laws is also critical, she said.

“Data is of prime importance and data governance and security is very, very critical in today’s day and age. So, if companies are putting in those laws and governances and deciding to use one over the other, I think as employees, we have to follow the governance policies,” she added.

That sentiment is echoed by a growing number of companies branding themselves “AI-first.” Several engineers said they’ve been explicitly told to adopt “AI-first coding” in internal meetings. A backend developer at a fintech company, seeking anonymity, said, “We were literally forced to do vibe coding for production-grade apps.”

For younger engineers, the risk is more personal. The early years that should have been about learning architecture, debugging, and understanding systems are now being spent fine-tuning prompts.

The post Indian Companies are Forcing Developers to Use Cursor appeared first on Analytics India Magazine.

Google on Tuesday announced a major expansion of its AI infrastructure and investments in India, unveiling new local compute capacity, AI tools, and collaborations designed to strengthen India’s digital and AI sovereignty.

The company said it is deploying its AI Hypercomputer architecture, powered by Trillium TPUs, within India to support businesses and public sector organisations in training and serving advanced Gemini models locally. The move aims to support India’s data residency and sovereignty requirements while reducing latency for AI workloads.

“India’s developer community, vibrant startup ecosystem, and leading enterprises are embracing AI with incredible speed,” said Saurabh Tiwary, vice president and general manager of Cloud AI at Google.

“To meet this moment for India, we are investing in powerful, locally available tools that can help foster a diverse ecosystem and ensure compliance with AI sovereignty needs.”

The company said that Gemini 2.5 Flash, already available to regulated Indian customers, now supports local machine learning processing. Google Cloud has also opened early testing for its latest Gemini models in India and committed to launching its most advanced versions with full data residency support, marking the first time Google Cloud will host such models locally.

The announcement also includes a suite of AI capabilities built for India’s context. These include batch support for Gemini 2.5 Flash to handle large-scale AI tasks cost-effectively, Document AI for automating document processing, and real-time grounding on Google Maps for location-aware responses.

In a move to strengthen India’s AI research ecosystem, Google Cloud and Google DeepMind announced a collaboration with IIT Madras to support the launch of Indic Arena, a benchmarking platform developed by the AI4Bharat centre. Indic Arena will allow users across India to anonymously evaluate and rank AI models on multilingual tasks unique to India’s linguistic diversity.

“At AI4Bharat, our mission is to build AI for India’s specific needs,” said Mitesh Khapra, Associate Professor at IIT Madras. “A critical part of this is having a neutral, standardised benchmark to understand how models are performing across our many languages. Indic Arena will be that platform.”

Tiwary said the new TPU infrastructure and research partnerships reflect Google’s commitment to India’s long-term AI ambitions. “We’re committed to bringing our latest AI advancements to India faster than ever, with the controls and capabilities that reflect the country’s unique business and cultural context,” he said.

Google invited startups, research institutions, and government organisations to leverage the new Trillium TPU-powered infrastructure through Vertex AI, aiming to help build AI systems “by Indians, for Indians.”

The post Google Brings Trillium TPUs to India to Power Local AI Growth appeared first on Analytics India Magazine.

Genpact has announced the appointment of Dinesh Jain as its global capability centre (GCC) lead on November 11, strengthening its focus on helping clients design, scale, and transform their GCC strategies, as per the release.

Based in Mumbai, Jain will lead Genpact’s global efforts to help enterprises evolve their GCCs into strategic growth engines powered by agentic operations, advanced technologies, and data-led transformation.

“In the era of agentic operations, GCCs are no longer just delivery hubs; they are strategic growth engines,” said Riju Vashisht, chief growth officer, Genpact. “With Dinesh’s leadership, we’re helping clients reimagine these centres as catalysts for continuous innovation and competitive advantage.”

In his new role, Jain will define and execute Genpact’s GCC strategy and playbooks, advising global clients on setting up, scaling, or transforming their centres into innovation, engineering, and process excellence hubs. He will also guide enterprises on scale or carve-out strategies to unlock long-term value.

“GCCs today sit at the intersection of process, technology, data, and global talent, shaping how businesses scale and compete,” Dinesh Jain, GCC lead, Genpact said.

Jain brings extensive experience in technology delivery and digital transformation, having worked with multinational organisations to architect and scale their global capability centres. Before joining Genpact, he led Accenture Technology GCC Solutions and Offering from Mumbai and held senior roles in transformation, technology strategy, architecture, and delivery.

Meanwhile, Genpact offers four key support areas. The first is innovation enablement, which helps GCCs adopt emerging technologies and redesign workflows. The second is governance and risk management, which includes compliance consulting and talent acquisition support.

The third is value realisation, which drives cost savings while unlocking enterprise value. Lastly, digital transformation support is essential for developing technology roadmaps and managing change.

The post Genpact Appoints Dinesh Jain as GCC Lead appeared first on Analytics India Magazine.