Technology

GTC felt more bullish than ever, but Nvidia’s challenges are piling up

Nvidia took San Jose by storm this year, with a record-breaking 25,000 attendees flocking to the San Jose Convention Center and surrounding downtown buildings. Many workshops, talks, and panels were so packed that people had to lean against walls or sit on the floor — and suffer the wrath of organizers shouting commands to get them to line up properly.

Nvidia currently sits at the top of the AI world, with record-breaking financials, sky-high profit margins, and no serious competitors yet. But the coming months also hold unprecedented risk for the company as it faces U.S. tariffs, DeepSeek, and shifting priorities from top AI customers.

At GTC 2025, Nvidia CEO Jensen Huang attempted to project confidence, unveiling powerful new chips, personal “supercomputers,” and, of course, really cute robots. It was an exhaustive sales pitch – one aimed at investors reeling from Nvidia’s nosediving stock.

“The more you buy, the more you save,” Huang said at one point during a keynote on Tuesday. “It’s even better than that. Now, the more you buy, the more you make.”

Inference boom

More than anything, Nvidia at this year’s GTC sought to assure attendees – and the rest of the world watching – that demand for its chips won’t slow down anytime soon.

During his keynote, Huang claimed that nearly the “entire world got it wrong” on traditional AI scaling falling out of vogue. Chinese AI lab DeepSeek, which earlier this year released a highly efficient “reasoning” model called R1, prompted fears among investors that Nvidia’s monster chips may no longer be necessary for training competitive AI.

But Huang has repeatedly insisted that power-hungry reasoning models will, in fact, drive more demand for the company’s chips, not less. That’s why at GTC, Huang showed off Nvidia’s next line of Vera Rubin GPUs, claiming they’ll perform inference (that is, run AI models) at roughly double the rate of Nvidia’s current best Blackwell chip.

The threat to Nvidia’s business that Huang spent less time addressing was upstarts like Cerebras, Groq, and other low-cost inference hardware and cloud providers. Nearly every hyperscaler is developing a custom chip for inference, if not training, as well. AWS has Graviton and Inferentia (which it’s reportedly aggressively discounting), Google has TPUs, and Microsoft has Cobalt 100.

GettyImages 2205761750 — **Image Credits:**Justin Sullivan / Getty Images

Along the same vein, tech giants currently extremely reliant on Nvidia chips, including OpenAI and Meta, are looking to reduce those ties via in-house hardware efforts. If they – and the aforementioned other rivals – are successful, it’ll almost assuredly weaken Nvidia’s stranglehold on the AI chips market.

That’s perhaps why Nvidia’s share price dipped around 4% following Huang’s keynote. Investors might’ve been holding out hope for “one last thing” — or perhaps an accelerated launch window. In the end, they got neither.

Tariff tensions

Nvidia also sought to allay worries about tariffs at GTC 2025.

The U.S. hasn’t imposed any tariffs on Taiwan (where Nvidia gets most of its chips), and Huang claimed tariffs wouldn’t do “significant damage” in the short run. He stopped short of promising that Nvidia would be shielded from the long-term economic impacts, however — whatever form they ultimately take.

Nvidia has clearly received the Trump Administration’s “America First” message, with Huang pledging at GTC to spend hundreds of billions of dollars on manufacturing in the U.S. While that would help the company diversify its supply chains, it’s also a massive cost for Nvidia, whose multitrillion-dollar valuation depends on healthy profit margins.

New business

As it looks to seed and grow businesses other than its core chips line, Nvidia at GTC drew attention to its new investments in quantum, an industry that the company has historically neglected. At GTC’s first Quantum Day, Huang apologized to the CEOs of major quantum companies for causing a minor stock crash in January 2025 after he suggested that the tech wouldn’t be very useful for the next 15 to 30 years.

GettyImages 2205217071 — **Image Credits:**David Paul Morris / Bloomberg / Getty Images

On Tuesday, Nvidia announced that it would open a new center in Boston, NVAQC, to advance quantum computing in collaboration with “leading” hardware and software markers. The center will, of course, be equipped with Nvidia chips, which the company says will enable researchers to simulate quantum systems and the models necessary for quantum error correction.

In the more immediate future, Nvidia sees what it’s calling “personal AI supercomputers” as a potential new revenue-maker.

At GTC, the company launched DGX Spark (previously called Project Digits) and DGX Station, both of which are designed to allow users to prototype, fine-tune, and run AI models in a range of sizes at the edge. Neither is exactly inexpensive – they retail for thousands of dollars – but Huang boldly proclaimed that they represent the future of the personal PC.

“This is the computer of the age of AI,” Huang said during his keynote. “This is what computers should look like, and this is what computers will run in the future.”

We’ll soon see if customers agree.

Technology

The Case for Custom eLearning Platforms: Why Organizations Are Making the Switch

aloe vera plant on grey pot on table with MacBook Pro and iPad

The corporate eLearning market has exploded in recent years, growing over 800% since 2000. As the demand for eLearning continues to accelerate, more and more organizations are finding that off-the-shelf solutions cannot keep pace with their training needs. This has led many companies to make the switch to custom-built eLearning platforms tailored specifically for their requirements.

There are several key reasons driving the demand for customized eLearning tools:

Greater Flexibility and Scalability

Generic eLearning software packages often impose rigid constraints that limit their ability to adapt to an organization’s evolving needs. Meanwhile, the “one-size-fits-all” approach fails to support the personalized learning critical for employee development. Custom platforms provide flexibility to add and modify features to match ever-changing business goals. As companies scale training across global workforces, custom solutions built on cloud infrastructure can scale seamlessly to handle growing demand.

Deeper Integration Across Systems

Smooth integration with existing HR, LMS, and other business systems is critical for optimizing training workflows. However, off-the-shelf tools rarely integrate well, creating data and process siloes. Custom platforms can tightly integrate role-based learning paths with core business applications, sync user profiles, enable single sign-on, and more. This level of integration catalyzes more impactful training function.

Better Data and Analytics

Generic software severely limits access to data insights that drive improvement. Custom platforms unlock a trove of analytics on content consumption, learner progression, platform adoption, and real-time feedback. Integrated analytics dashboards and APIs allow businesses to derive deep visibility across the learner lifecycle. These insights help continuously enhance learner experience, target development gaps, and demonstrate direct training ROI.

Enhanced Learner Engagement

For modern learners accustomed to consumer-grade digital experiences, poor platform usability quickly erodes engagement. Custom designs allow companies to incorporate familiar features from popular apps and websites while optimizing for their audience. Adaptive learning approaches further personalize content to individual styles and needs. With modular component architecture, custom platforms stay on the cutting edge of new modalities like AR/ VR to captivate learners.

Brand and Culture Alignment

Off-the-shelf tools impose a generic and often disruptive experience that clashes with existing brand identity and culture. In contrast, custom platforms allow organizations to carry over familiar styling, voice, and workflow patterns. Consistency in experience preserves brand recognition while smoother onboarding leads to wider adoption across all employee groups. Over time, the platform can evolve alongside cultural changes as well.

While custom elearning tools require greater upfront investment, for enterprise training needs, the long-term benefits far outweigh the costs. The ability to mold platforms to current and future needs results in greater leverage from learning spend.

As businesses demand ever-more from their learning technology, custom solutions provide the agility needed for true scale. Rather than forcing training functions into the constraints of generic software, custom elearning development keeps the focus on nurturing talent and capabilities. For any organization looking to drive workforce transformation through learning, custom elearning represents the way forward.

Technology

Pintarnya raises $16.7M to power jobs and financial services in Indonesia

Pintarnya, an Indonesian employment platform that goes beyond job matching by offering financial services along with full-time and side-gig opportunities, said it has raised a $16.7 million Series A round.

The funding was led by Square Peg with participation from existing investors Vertex Venture Southeast Asia & India and East Ventures.

Ghirish Pokardas, Nelly Nurmalasari, and Henry Hendrawan founded Pintarnya in 2022 to tackle two of the biggest challenges Indonesians face daily: earning enough and borrowing responsibly.

“Traditionally, mass workers in Indonesia find jobs offline through job fairs or word of mouth, with employers buried in paper applications and candidates rarely hearing back. For borrowing, their options are often limited to family/friend or predatory lenders with harsh collection practices,” Henry Hendrawan, co-founder of Pintarnya, told TechCrunch. “We digitize job matching with AI to make hiring faster and we provide workers with safer, healthier lending options — designed around what they can reasonably afford, rather than pushing them deeper into debt.”

Around 59% of Indonesia’s 150 million workforce is employed in the informal sector, highlighting the difficulties these workers encounter in accessing formal financial services because they lack verifiable income and official employment documentation.

Pintarnya tackles this challenge by partnering with asset-backed lenders to offer secured loans, using collateral such as gold, electronics, or vehicles, Hendrawan added.

Since its seed funding in 2022, the platform currently serves over 10 million job seeker users and 40,000 employers nationwide. Its revenue has increased almost fivefold year-over-year and expects to reach break-even by the end of the year, Hendrawn noted. Pintarnya primarily serves users aged 21 to 40, most of whom have a high school education or a diploma below university level. The startup aims to focus on this underserved segment, given the large population of blue-collar and informal workers in Indonesia.

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“Through the journey of building employment services, we discovered that our users needed more than just jobs — they needed access to financial services that traditional banks couldn’t provide,” said Hendrawan. “We digitize job matching with AI to make hiring faster and we provide workers with safer, healthier lending options — designed around what they can reasonably afford, rather than pushing them deeper into debt.”

Pintarnya Founders Press Kit — image credits: Pintarnya (Founders of Pintarnya Ghirish Pokardas, Nelly Nurmalasari, and Henry Hendrawan)

While Indonesia already has job platforms like JobStreet, Kalibrr, and Glints, these primarily cater to white-collar roles, which represent only a small portion of the workforce, according to Hendrawan. Pintarnya’s platform is designed specifically for blue-collar workers, offering tailored experiences such as quick-apply options for walk-in interviews, affordable e-learning on relevant skills, in-app opportunities for supplemental income, and seamless connections to financial services like loans.

The same trend is evident in Indonesia’s fintech sector, which similarly caters to white-collar or upper-middle-class consumers. Conventional credit scoring models for loans, which rely on steady monthly income and bank account activity, often leave blue-collar workers overlooked by existing fintech providers, Hendrawan explained.

When asked about which fintech services are most in demand, Hendrawan mentioned, “Given their employment status, lending is the most in-demand financial service for Pintarnya’s users today. We are planning to ‘graduate’ them to micro-savings and investments down the road through innovative products with our partners.”

The new funding will enable Pintarnya to strengthen its platform technology and broaden its financial service offerings through strategic partnerships. With most Indonesian workers employed in blue-collar and informal sectors, the co-founders see substantial growth opportunities in the local market. Leveraging their extensive experience in managing businesses across Southeast Asia, they are also open to exploring regional expansion when the timing is right.

“Our vision is for Pintarnya to be the everyday companion that empowers Indonesians to not only make ends meet today, but also plan, grow, and upgrade their lives tomorrow … In five years, we see Pintarnya as the go-to super app for Indonesia’s workers, not just for earning income, but as a trusted partner throughout their life journey,” Hendrawan said. “We want to be the first stop when someone is looking for work, a place that helps them upgrade their skills, and a reliable guide as they make financial decisions.”

Technology

OpenAI warns against SPVs and other ‘unauthorized’ investments

In a new blog post, OpenAI warns against “unauthorized opportunities to gain exposure to OpenAI through a variety of means,” including special purpose vehicles, known as SPVs.

“We urge you to be careful if you are contacted by a firm that purports to have access to OpenAI, including through the sale of an SPV interest with exposure to OpenAI equity,” the company writes. The blog post acknowledges that “not every offer of OpenAI equity […] is problematic” but says firms may be “attempting to circumvent our transfer restrictions.”

“If so, the sale will not be recognized and carry no economic value to you,” OpenAI says.

Investors have increasingly used SPVs (which pool money for one-off investments) as a way to buy into hot AI startups, prompting other VCs to criticize them as a vehicle for “tourist chumps.”

Business Insider reports that OpenAI isn’t the only major AI company looking to crack down on SPVs, with Anthropic reportedly telling Menlo Ventures it must use its own capital, not an SPV, to invest in an upcoming round.