CAMB.AI is introducing its new Streaming SDK and Streaming Dashboard at IBC2026, with integrations into NVIDIA Holoscan for Media open reference architecture
The release gives developers and broadcast teams new ways to integrate, manage and deploy real-time multilingual broadcasting within their existing workflows.
Multilingual broadcasting, now live as an SDK
Available for C++, Python, Java and Rust, the SDKs allow developers to start broadcasting in multiple languages with as little as three lines of code, making it easier to integrate multilingual capabilities directly into existing applications and workflows.
CAMB.AI’s live streaming platform supports 150+ languages, producing dubbed audio and subtitles for live content. It supports source-speaker voice cloning, studio voices and custom terminology, allowing names, venues, sponsors and other specific terminology to remain consistent across languages.
The release features the latest quality enhancements backed by CAMB’s foundational models MARS and BOLI.
Bringing live dubbing to NVIDIA Holoscan for Media open reference architecture
CAMB.AI’s new capabilities will be available within the NVIDIA Holoscan for Media reference architecture as a hybrid SaaS.
Holoscan for Media is NVIDIA’s open reference architecture and developer toolkit for building AI-powered live media solutions on NVIDIA infrastructure.
Program audio can be processed by CAMB.AI’s models to produce dubbed commentary in each target language, with outputs returned to the production network or delivered directly to destinations including CDN, OTT and YouTube Live.
For broadcasters, this allows live localization to operate alongside other production applications. It reduces the need to send feeds to a separate cloud localization environment and back, reducing infrastructure hops while allowing media to remain within the broadcaster’s facility or own cloud environment when required.
New Streaming Dashboard
The new Streaming Dashboard provides a visual environment for building, launching and monitoring multilingual streams.
Operators can configure sources, select audio, set processing profiles, create language pipelines and manage output destinations from a single interface. During a live broadcast, teams can monitor stream health, outputs, runtime and live transcripts, as well as pause and resume dubbing without stopping the stream.
CAMB.AI’s live localization technology has already been used across Ligue 1+, NASCAR and Eurovision Sport, including live AI-dubbed commentary and multilingual subtitling.
See It at IBC2026
CAMB.AI will preview its new dashboard and SDKs at IBC2026. Visitors will be able to see live multilingual dubbing in action at the CAMB.AI booth.
CAMB.AI builds localization AI for content, entertainment and sport.
Its MARS family of speech models and livestreaming platform deliver dubbing, translation and subtitles in more than 150 languages, live and on demand.
Founded in 2022, CAMB.AI has offices in Dubai and San Francisco.
Robert Way
Hyperscalers and Nvidia (NVDA) had become a much larger source of long-duration debt issuance relative to the U.S. Treasury in 2026, according to a chart posted by Global Macro.
The chart showed hyperscaler and Nvidia debt issuance, including special-purpose vehicles, had risen
Key deals this week: Flex, Nvidia, AbbVie and more
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U.K. artificial intelligence cloud computing firm Nscale is looking to raise $3.5B in new financing, with Nvidia (NVDA) and hedge fund Third Point likely participating, Bloomberg reported.
Nscale could sell as much as $1.5B in convertible notes, and Third Point, which is run
Nvidia CEO Jensen Huang (right) visits an internet cafe with NCSoft CEO Kim Taek-jin in Seoul, South Korea, on June 7. Huang announced in a blog post on Thursday that his company is acquiring Hugging Face for $12.9 billion. File Photo by Yonhap/EPA
Sept. 3 (UPI) — Nvidia announced on Thursday that it has agreed to acquire open-source AI company Hugging Face for $12.9 billion.
The acquisition will bring a platform that is used by 18 million people, including researchers and developers, under Nvidia’s ownership. Hugging Face has been used to share more than 3 million models, 500,000 datasets and 1 million applications, Nvidia said in a blog post.
“Over the past decade, Clem [Delangue], Julien [Chaumond], Thomas [Wolf] and the team at Hugging Face have built something remarkable: a vibrant home for the open model developer community,” Jensen Huang, founder and CEO of Nvidia, wrote in the blog post. “Hugging Face will remain an open platform for the entire AI ecosystem. Developers will choose the models they want, the frameworks they want, the clouds and inference service providers they want and the computing platforms they want.”
Nvidia adds that Nvidia compute will not be required to use Hugging Face.
In July, Hugging Face was targeted by OpenAI chatbots that went rogue, hacking the firm in what was described as a “security incident.”
OpenAI said its engineers had asked AI models to find solutions for ExploitGym, a benchmark that tests AI agents’ capability to exploit vulnerabilities in a system. The models were meant to perform this task within a sandbox but escaped, accessing the open internet and ultimately restricted information.
With restricted information, the AI models were able to cheat the vulnerabilities test and obtain an access code from Hugging Face’s servers.
Hugging Face CEO Delangue said there was “no malicious intent” by OpenAI. OpenAI said it took containment actions in response to the incident.
Nvidia CEO excluded in TIME’s 100 most influential people in AI
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Nvidia posted quarterly revenue of $96.2 billion (€82.4bn) on Wednesday, comfortably beating the $92.2 billion (€79bn) Wall Street had expected, as chief executive Jensen Huang declared that artificial intelligence had reached “its inflection point” and guided next quarter revenue to $108 billion (€92.5bn) — again, above forecasts.
“AI has reached its inflection point,” Huang said in a statement. “It’s doing useful work. Its tokens are productive and profitable. Now, compute is revenue, and demand is accelerating.”
Shares initially dipped after the release before recovering in after-hours trading.
Days on which Nvidia reports its quarterly results have an outsized importance for the world’s most valuable company.
At a market capitalisation north of $5 trillion (€4.3tn) it is the most valuable company in the world, worth more than the GDP of Japan, the fourth largest economy in the world.
Yet there is a strange rite that plays out each quarter: Nvidia beats expectations, and the stock falls anyway. It happened after the first-quarter beat this year, when shares slid close to 5% in the days that followed.
The pattern has left a dynamic where the company needs to significantly outperform an already-bullish consensus, or provide a stronger-than-expected outlook, to move the share price higher.
The main concern around Nvidia is not whether it can grow; it is more of a question of who it is growing for.
The firm still draws the bulk of its revenue from Amazon, Google and Microsoft, each of which is now designing its own chips to reduce reliance on the company. The new disclosure will show precisely how large that dependence remains.
Chief Executive Jensen Huang’s commentary on demand into 2027 therefore carries more weight than any single figure. The question has grown sharper since July, when markets fell on doubts about whether vast AI investments will ever generate proportionate returns.
Nvidia’s answer has been to help finance the buildout itself. This month alone it assembled a $500bn (€428bn) capital pool with six Wall Street asset managers for data centre projects, and separately committed up to $105bn (€90bn) to back an OpenAI data centre in Pike County, Ohio, with an initial capacity of 4.25 gigawatts and an option for a further 3.75.
Export policy to China has been one of the most volatile threads in Nvidia’s recent history and is likely to feature heavily on the earnings call.
Washington barred sales of the China-specific H20 chip in April 2025, reversed course, and Nvidia has since received approval to ship the more capable H200 chip to vetted Chinese customers.
Reports have surfaced of large allocations to ByteDance and Tencent, though Beijing has been encouraging domestic firms to limit their purchases and prioritise homegrown alternatives.
Nvidia’s current growth is being driven by its Blackwell chips, the generation of processors powering most AI data centres today. Their successor, known as Vera Rubin, is expected to begin shipping in the second half of the year.
Nvidia has a tradition of naming its chip architectures after scientists and past generations include Ampere, named after physicist André-Marie Ampère; Hopper, named after computer scientist Grace Hopper; and the current Blackwell chip named after mathematician David Blackwell.
Vera Rubin continues that pattern. She was an American astronomer whose observations of how galaxies rotate provided some of the strongest early evidence for the existence of dark matter, the invisible mass thought to make up much of the universe. She died in 2016 and is widely seen as someone who was overlooked for a Nobel Prize during her lifetime,
The company has pointed to an order backlog it says is worth around $1 trillion (€857bn) across 2026 and 2027, though that figure comes from company commentary rather than independently verified financial disclosure.
Wednesday’s data offered no relief on inflation.
The personal consumption expenditures index, the Federal Reserve’s preferred gauge, rose 0.2% in July against expectations of 0.1%, leaving the annual rate at 3.7% rather than easing to the 3.6% forecast. Core prices held at 3.3% over the year, above the Fed’s 2% target for a 65th consecutive month.
The Federal Open Market Committee held rates at 3.50% to 3.75% in July, with three regional Fed presidents dissenting in favour of a quarter-point increase.
Markets currently put the probability of a September hike at around 40%.
Attention now shifts to Jackson Hole, where Fed Chair Kevin Warsh delivers his keynote on Friday morning, his first since taking office in May, 19 days before the next rate decision. The ECB’s Isabel Schnabel joins a panel the same afternoon.
US stock markets drifted through a quiet session on Wednesday after data showed inflation last month was a touch higher than economists had expected.
The S&P 500 edged down less than 0.1% and remains near the all-time high it set earlier this month. The Dow Jones Industrial Average dipped 0.2% and the Nasdaq composite slipped 0.1%.
Treasury yields ticked higher after the inflation update, which has traders still largely betting the Federal Reserve will raise the federal funds rate before the end of this year. Oil prices fell after another volatile session.
Robert Way
An image made with a drone shows an Amazon Web Services data center in Ashburn, Va., on Sept. 23, 2025. File Photo by Jim Scalzo/EPA
Aug. 17 (UPI) — Nvidia announced on Monday that it will finance an OpenAI data center in Ohio for up to $105 billion.
The credit from Nvidia will fund the data center’s first 4.25 gigawatts in computing capacity with an option to bring 3.75 gigawatts more online. The center is slated to begin operating in Pike City, Ohio, in 2028.
The data center will be located at the PORTS-Pike Technology Campus in Pike City. It will be constructed and managed by SB Energy, a subsidiary of SoftBank Group.
Nvidia is also providing the compute power to the data center.
“This is the essential economic point: the [Load Power Supply] commitment secures a long-lived AI factory site, while the NVIDIA compute inside can be upgraded repeatedly,” NVIDIA said in a press release. “Each new generation can deliver greater production, more intelligence and better economics.”
SB Energy and SoftBank agree to build enough power supply for 10 gigawatts of energy and invest at least $4.2 billion into the regional power grid infrastructure. Nvidia has also agreed to invest $1.5 billion into SB Energy.
OpenAI said the data center will support 35,000 construction jobs through 2032. It will also support 2,500 long-term jobs.
OpenAI will pay the least on the data center as its tenant, Nvidia said.
Nvidia has recruited Wall Street to bankroll its own customers.
The US chipmaker said last week it had signed memorandums of understanding with Wall Street’s largest asset managers, including Apollo Global Management, Blackstone, BlackRock, Brookfield Asset Management, Goldman Sachs and KKR to raise upwards of half a trillion dollars for AI companies to borrow against, money that will buy its chips and build the servers that run them.
The six firms will set up what Nvidia calls “compute financing platforms,” drawing on institutional money, insurance funds and private credit. Borrowers can use the proceeds for the chips as well as servers, networking equipment, buildings and power supply.
Nvidia has the option to guarantee up to a quarter of any given deal, which lowers the interest rate its customers pay while leaving most of the credit risk with the lenders.
CEO Jensen Huang said he approached only these six companies and none refused.
Keeping that spending off their own books is precisely the point, and the fact that such a structure is needed at all tells investors a great deal about where the constraints in the AI boom now lie.
The financial engineering rests on a single reclassification. Graphics processing units (GPUs) have always been treated as equipment that loses value quickly, superseded whenever a faster generation arrives.
Nvidia is effectively asking lenders to treat them instead as long-lived infrastructure, closer to a toll road or a power plant, that can be borrowed against for years.
“These are revenue-generating assets now,” Huang said, describing them as productive, long-lived and transferable between customers.
The timing reflects a squeeze that has been building all year.
Microsoft, Amazon, Alphabet, Meta and other hyperscalers whose cloud platforms host most of the world’s AI workloads have together guided roughly $720 billion (€624bn) to $745 billion (€646bn) of capital spending in 2026, an increase of about 77% on last year.
What analysts expect the hyperscalers to spend in 2027 alone has more than doubled in the space of a year, from a consensus of $480 billion (€416bn) in August 2025 to $1.08 trillion (€943bn) this month, a rise of about 127%, according to Bank of America.
The pattern has repeated at every stage.
Analysts who already considered last year’s investment unsustainable then watched the hyperscalers guide higher at the start of 2026, revise those figures upward again through the year, and pencil in larger sums still for next year and 2028.
Moody’s has warned that spending on this scale is eating into free cash flow and pushing tech groups into heavier borrowing. Alphabet recorded negative free cash flow of $5.9 billion (€5.1bn) in a quarter when it spent $44.9 billion (€38.9bn) on projects.
That is the pressure the structure of Nvidia’s Wall Street deal relieves.
Debt raised through these “compute financing platforms” sits with the financing vehicles rather than on a hyperscaler’s own accounts and also has Nvidia’s backing, which protects credit ratings and leaves room for conventional borrowing elsewhere.
For smaller operators the effect is larger still as companies such as CoreWeave and Nebius, which lack investment-grade ratings and pay dearly for credit, gain access to capital on terms previously reserved for the giants.
The reaction was more ambivalent than the headline number suggests, and came weeks after a July selloff driven by doubts over whether AI spending will pay for itself.
Essentially, equity investors saw a bottleneck being cleared while credit investors saw something else: the cost of insuring Nvidia’s own debt against default rose after the news and has roughly doubled since late May.
Their doubt concentrates on the reclassification previously mentioned.
“Chips depreciate fast and lose value the moment a newer generation arrives,” warned Nigel Green of financial advisory firm deVere Group, noting that lending against them only works if the collateral holds its value.
Critics also point out that Nvidia is helping finance purchases of its own products, deepening the circularity that already worries the sector.
Goldman Sachs CEO David Solomon called it “a pivotal moment of a historic AI investment cycle.”
Whether it proves pivotal in the direction Solomon means depends on a question nobody can yet answer: what will the value of a current GPU be in five years?
