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OpenAI Reportedly in Talks to Raise $30 Billion at $1.4 Trillion Valuation Ahead of IPO

By
Samuel Nwite
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OpenAI is in talks with investors to raise at least $30 billion in a new funding round that could value the ChatGPT maker at roughly $1.4 trillion, Bloomberg reported on Tuesday, underpinning the enormous capital requirements surrounding the development and commercialization of frontier artificial intelligence.

The proposed financing would come as investors seek exposure to OpenAI ahead of an anticipated eventual public listing. If completed at the reported valuation, the round would represent a substantial increase from the company’s most recent private valuation of $852 billion.

OpenAI raised $122 billion in March at that valuation in what was expected to be its final private funding round before an initial public offering. The company had previously been expected to pursue a listing as early as this year, but CEO Sam Altman has since ruled out an IPO in 2026.

The reported new financing would instead serve as a bridge to a future public offering, Bloomberg reported.

The scale of the proposed round highlights the extraordinary financing requirements of OpenAI’s strategy. Unlike conventional software companies, frontier AI developers must continuously invest in computing capacity, data centers, chips, model training, and research as they compete to develop increasingly capable systems.

Investor interest has also been supported by rapid growth in OpenAI’s revenue.

Bloomberg reported that OpenAI’s run-rate revenue reached $40 billion in August, representing a 70% increase since July. The growth followed a strategic refocus on areas including coding, after Anthropic briefly moved ahead of OpenAI earlier in the year in some areas of the AI market.

The acceleration in revenue gives investors a more tangible measure of the commercial demand supporting OpenAI’s valuation.

The company has also been expanding beyond ChatGPT’s consumer business into enterprise software, developer tools and AI agents. Its strategy involves making its models available across a wider range of applications while using its enormous user base to create additional distribution opportunities.

That expansion is occurring alongside rapidly escalating spending across the AI industry.

OpenAI’s valuation is believed to lie not only on its current revenue but on expectations that demand for AI computing and services will continue expanding rapidly enough to justify the capital being deployed.

A $30 billion financing would provide OpenAI with another substantial pool of private capital before it eventually turns to public markets.

The reported fundraising also comes as OpenAI continues to grapple with concerns over the safety of smart AI models.

Altman has said the company will not pursue an IPO in 2026, with safety remaining a priority.

“I think it is unacceptable to be taking like a 10% chance of killing everybody by the end of the decade,” Altman recently told Fortune, responding to warnings from AI safety researchers about existential risks associated with powerful systems.

The decision to remain private for longer gives OpenAI additional time to develop its technology and address safety issues without the immediate reporting and market pressures associated with being a publicly traded company.

At the same time, delaying an IPO means the company must continue relying on private investors to finance an exceptionally capital-intensive expansion.

The reported $1.4 trillion valuation would place OpenAI among the world’s most highly valued private technology companies. It would also represent an increase of about 64% from the $852 billion valuation attached to its March financing.

However, analysts expect that jump to put pressure on OpenAI to demonstrate that its rapid revenue growth can eventually translate into sustainable economics capable of supporting the valuation.

The proposed financing, if completed, would give the company another bridge between its current private-market expansion and a future public listing, while allowing it to continue investing heavily in the computing infrastructure and AI research required to compete with Anthropic, Google, Meta and other major developers.

Goldman Sachs Interns Reveal What Young Workers Think About AI as Microsoft Copilot Chief Warns of AI Risks

By
Paul Ugbede Godwin
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Artificial intelligence is becoming less a question of whether it will change work than of what people still want technology to leave untouched.

Goldman Sachs’ annual intern survey and an interview with Microsoft’s Copilot chief Jacob Andreou—offer an unusually revealing view of that tension. One comes from young professionals entering Wall Street; the other from an executive helping shape one of the world’s largest AI platforms.

Goldman Sachs surveyed more than 2,100 interns in its 2026 annual survey, giving a glimpse into how a generation raised with digital technology is approaching AI.

The results suggest that these young workers are neither blindly enthusiastic nor broadly fearful. Instead, they appear to be drawing boundaries around where AI is useful and where human involvement remains important.

The interns are comfortable using AI as a practical tool. Many use it for learning, writing and coding, while 71% support AI being used for financial activities such as budgeting and investment advice.

Yet that enthusiasm changes when technology enters creative territory. About 60% opposed AI involvement in areas such as art, music and books, an increase from the previous year. That distinction matters.

Digital natives, as Goldman Sachs itself has noted, do not necessarily want a digital-only world. The survey indicates that young professionals still place considerable value on human interaction.

Forty-two percent prefer collaborating in person, while hands-on learning ranked more highly than AI-assisted learning. Mentorship, spontaneous conversations and relationships remain part of what they expect from professional life.

Their optimism is also striking. Sixty-three percent of respondents described themselves as very positive about their own futures, even as they were more cautious about the broader U.S. job market.

Their aspirations remain remarkably traditional: stable relationships, home ownership and a sustainable personal life alongside ambitious careers.

Microsoft’s Andreou approaches the same technological transformation from the opposite side of the table. His biggest concern is not primarily an AI system becoming too powerful. Instead, he worries about how the economic benefits of AI will be distributed.

In an interview, Andreou identified the equitable diffusion of AI as Microsoft’s central concern. His fear is that advanced AI could become concentrated among a small number of powerful companies, producing greater economic consolidation and inequality rather than broadly shared productivity gains.

That concern arrives as Microsoft pushes Copilot deeper into everyday work. The company says Microsoft 365 Copilot has surpassed 30 million paid seats, while newer agentic systems can plan, execute, test and correct multistep tasks.

Microsoft is increasingly presenting AI not simply as an assistant but as an active participant in organizational workflows. The contradiction is therefore becoming clearer.

Workers want AI to remove tedious tasks, improve productivity and expand opportunity, but they do not necessarily want it to replace human judgment, relationships or creativity.

Meanwhile, technology companies face a parallel challenge: making increasingly powerful systems widely accessible without allowing their economic value to become concentrated.

The future of AI may depend on resolving both questions. Goldman’s interns are asking where technology should stop. Microsoft is asking who gets to benefit when it continues forward.

Those questions point toward the real AI debate—not simply how intelligent machines can become, but how humans choose to integrate them into work, creativity and society.

ZachXBT Links Chinese Actors to $387M Bitget Hack Laundering as NEAR Intent Prevented $50M in Flows

By
Paul Ugbede Godwin
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The $387.5 million Bitget exploit has quickly become more than another crypto exchange hack. It is now a case study in how stolen digital assets move through a fragmented, cross-chain financial system—and how blockchain investigators and decentralized infrastructure providers are attempting to disrupt that process in real time.

Bitget confirmed that approximately $387.5 million in assets were transferred to attacker-controlled addresses during the September 24 breach, revising its original estimate of $351.6 million after identifying additional losses involving Zcash and TRON.

The exchange said the incident was contained and that its User Protection Fund would cover affected users. The laundering trail has since attracted the attention of blockchain investigator ZachXBT.

He alleged that Chinese illicit actors are helping launder funds connected to the suspected North Korean attackers, with some of the alleged intermediaries openly seeking transaction assistance through Discord servers and Telegram channels associated with services they were using.

ZachXBT also linked one alleged operator to an earlier $292 million Kelp DAO exploit.  The attribution remains an allegation rather than a final judicial determination. Bitget has publicly pointed toward a North Korean connection, while investigations continue.

The important issue for the crypto industry, however, is the laundering infrastructure exposed by the investigation. According to reporting on ZachXBT’s findings, the stolen assets were moved between blockchains using bridges before being routed toward privacy-oriented services.

This strategy illustrates the fundamental challenge facing investigators: blockchain transactions are transparent, but liquidity is increasingly distributed across networks, bridges, decentralized exchanges, solvers and privacy tools.

That is where NEAR Intents enters the story. NEAR Intents said its SHIELD risk-intelligence system detected more than $50 million in attempted Bitget-linked flows. Most of those transactions were rejected before execution.

Approximately $503,000 was frozen during execution, while around $166,000 passed through the infrastructure, according to NEAR’s reported figures. The distinction matters. NEAR Intents did not seize $50 million.

Rather, its system prevented more than $50 million in attempted flows from being processed, while separately freezing funds that had already entered the execution process. The rejected transactions could then be redirected toward other venues.

NEAR’s response also highlights an emerging model for decentralized finance: permissionless networks do not necessarily require every application, liquidity provider or solver to process every transaction.

SHIELD can use intelligence from transaction-monitoring providers, researchers, exchanges and other industry participants to identify suspicious activity and refuse certain requests.

Perhaps more significant was NEAR Intents’ decision to waive its potential bounty share. Bitget had established a recovery program, but NEAR said it would not claim a reward for the intervention, allowing more potential recovery value to remain with the exchange and its users. Bitget CEO Gracy Chen publicly acknowledged the contribution.

The episode therefore exposes two sides of crypto’s architecture. The same interoperability that allows legitimate users to move capital rapidly across networks can also provide attackers with multiple routes for dispersing stolen assets.

Yet that infrastructure can simultaneously become a surveillance and intervention layer when transaction intelligence is embedded directly into execution systems.

For the industry, the Bitget incident demonstrates that recovering stolen cryptocurrency is no longer solely a matter of tracing wallets after the fact. It increasingly depends on whether bridges, solvers, exchanges and decentralized protocols can recognize illicit flows quickly enough to prevent them from becoming irreversible.

Bitcoin ETFs Extend Inflow Streak to 8 Days as $31.1 Million Enters Spot Funds

By
Paul Ugbede Godwin
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0

Bitcoin’s spot exchange-traded funds are continuing to attract capital, with the latest $31.1 million in net inflows extending their positive streak to eight consecutive trading days.

While the daily figure is modest compared with some of the much larger flows seen during periods of aggressive institutional accumulation, the persistence of buying offers an important signal about investor positioning in the digital-asset market.

The eight-day streak matters because ETF flows provide a relatively direct window into institutional and traditional-market demand for Bitcoin. Rather than relying solely on exchange activity or derivatives positioning, investors can use spot Bitcoin ETFs to gain exposure through familiar regulated investment products.

Continued inflows therefore suggest that a portion of capital allocated through these vehicles remains committed to Bitcoin despite fluctuations in price and broader uncertainty across financial markets.

The $31.1 million inflow also arrives during a period in which Bitcoin’s market narrative is increasingly connected to macroeconomic conditions. Interest rates, Treasury yields, inflation expectations and liquidity remain important variables for risk assets, including cryptocurrencies.

When investors anticipate easier financial conditions, demand for assets with higher volatility can strengthen. Conversely, elevated yields and tighter liquidity can encourage investors to reduce exposure to speculative markets.

Against that backdrop, the ETF streak becomes more significant than the size of any single day’s inflow. Eight consecutive sessions of net buying indicate that demand has remained positive rather than being driven by one isolated institutional transaction.

However, the figure should not be interpreted as evidence that all investors are becoming more bullish. ETF flows represent aggregate net activity and can conceal substantial differences among individual funds, investors and trading strategies.

Bitcoin’s broader market structure also remains important. Institutional flows can influence available liquidity because spot ETFs generally require underlying Bitcoin exposure to support their products.

Sustained demand can therefore contribute to buying pressure in the spot market, particularly when new allocations are large relative to available liquidity. At the same time, ETF inflows do not guarantee a sustained price increase.

Investors can enter and exit positions for different reasons, and Bitcoin remains sensitive to leverage, derivatives positioning, macroeconomic news and changes in risk appetite.

For traders, the current streak may reinforce the importance of watching ETF flows alongside price action rather than treating either metric independently. If Bitcoin rises while ETF inflows accelerate, the combination could indicate stronger demand behind the move.

If prices weaken despite continued inflows, it could suggest that selling pressure elsewhere in the market remains substantial. Likewise, a sudden reversal from inflows to outflows could become an important indicator of changing institutional positioning.

The eight-day run therefore represents a small but notable piece of the larger Bitcoin investment story. The $31.1 million figure is not extraordinary by itself, but consistency can sometimes matter more than magnitude.

After years of debate over whether institutional investors would maintain meaningful exposure to Bitcoin, the continued use of regulated ETF products provides an increasingly important channel between traditional finance and the cryptocurrency market.

As Bitcoin navigates changing liquidity conditions, monetary policy expectations and volatile investor sentiment, the next several trading sessions will show whether the current ETF inflow streak can continue.

For now, eight consecutive days of net inflows indicate that demand through the spot ETF market remains positive, even as investors continue to weigh Bitcoin against the broader risks and opportunities across global financial markets.

UEFA Super Cup Final Win By Paris Saint Germain Settles Victory Odds

By
TI Partners
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0

In the 2025 UEFA Super Cup, Paris Saint-Germain completed a dramatic comeback against Tottenham in Udine. The 2-2 draw sent the UEFA Super Cup final into penalties. Paris then won 4-3 to secure its first Super Cup trophy. The result also settled pre-match victory markets around the European showpiece.

Paris Saint-Germain Turns Two-Goal Deficit Into Victory

Paris Saint-Germain entered the final after winning its first Champions League crown. Tottenham arrived after claiming the Europa League trophy. The matchup also provided several betting reference points for users visiting cambodia.1xbet.com/en/mobile while following the wider European football schedule. Both clubs therefore carried strong European form into the contest.

The match quickly developed into an important result for sports betting markets. Tottenham controlled the score after goals from Micky van de Ven and Cristian Romero. Van de Ven scored during the 39th minute from close range.

Romero then doubled Tottenham’s advantage shortly after halftime. His header arrived during the 48th minute of play. Paris faced a two-goal deficit with the match approaching its final stages.

The comeback began during the 85th minute through Kang-in Lee. His long-range strike gave Paris fresh momentum. Fourteen minutes later, Gonçalo Ramos completed the remarkable recovery.

Ramos headed home during the fourth minute of added time. Ousmane Dembélé created the chance with an excellent cross. UEFA later named Dembélé the Player of the Match. The final whistle arrived with both teams level at 2-2. Neither side could claim victory during regular playing time. The outcome therefore moved into a penalty shootout.

What The Result Meant For Sports Betting Markets

Sports betting markets separate match results from specific settlement conditions. Market settlement can differ by bet type, a distinction that also matters to bettors who have completed account registration before following major football fixtures. The final score settled the regular-time result at 2-2. The trophy winner then became Paris after the penalty shootout.

That distinction matters when reviewing different pre-match betting markets. A match-result market can use regular time as its settlement point. A tournament-winner market follows the team lifting the trophy.

The Super Cup final provided a clear example of this difference. Paris failed to lead after 90 minutes of football. However, the club still became the official competition winner.

Key figures from the final included:

  • Paris Saint-Germain scored two goals after halftime.
  • Tottenham scored both goals before the 50-minute mark.
  • Paris recorded 12 total attempts during the match.
  • Tottenham produced 13 total attempts across the contest.
  • Paris placed three attempts on target.
  • Tottenham placed five attempts on target.
  • The penalty shootout finished 4-3 for Paris.
  • Attendance at Stadio Friuli reached 21,025 spectators.

Late Goals Changed The Shape Of Victory Markets

The timing of Paris’s goals created the most dramatic part of the final. Lee scored with only five minutes remaining. Ramos then equalised during stoppage time. Those moments dramatically changed the match state within nine minutes. Markets connected with live match conditions therefore faced rapid changes.

Sports betting markets often react immediately to goals and major events. A two-goal lead creates a very different price than a level score. Paris moved from chasing the match toward forcing penalties.

The final penalty sequence added another layer to the result. Vitinha missed Paris’s opening penalty during the shootout. Tottenham then gained an opportunity to take control. Van de Ven failed to convert his attempt for Tottenham. Mathys Tel also missed during the decisive sequence. Those misses opened the door for Paris to complete its comeback.

That achievement added another significant data point for sports betting coverage. European competition results often influence future market expectations. Recent trophy success can become part of statistical team analysis.

Player Performances Added Important Betting Data

Individual performances also supplied useful information for sports betting analysis. Dembélé played a major role during Paris’s late recovery. His cross created Ramos’s equalising header during stoppage time. He then converted Paris’s third penalty during the shootout. UEFA’s technical observers subsequently selected him as Player of the Match.

Lee also became central to the comeback after entering the contest. His 85th-minute strike reduced the deficit to one goal. Ramos completed the scoring sequence with his late header. Lucas Chevalier also played an important role for Paris. The goalkeeper saved Van de Ven’s penalty during the shootout. That save directly affected the final trophy outcome.

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