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DeepSeek’s overnight fame strains its systems, draws attacks

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Talk of an artificial-intelligence upstart in China behind a formidable ChatGPT rival had been building for days. 

At the World Economic Forum in Davos last week, some mentioned Hangzhou-based DeepSeek and its recently released R1 model as a prime reason for countries such as the U.S. to be doubling down on AI advancements. On tech chat boards, engineers had begun comparing its programming performance to leading models from the likes of OpenAI and Microsoft Corp. Its product quietly rose through the ranks of top performers on a UC Berkeley-affiliated AI leaderboard. 

Then, within the past 36 hours, interest in the startup exploded. Silicon Valley heavyweights including investor Marc Andreessen and AI godfather and chief Meta Platforms Inc. scientist Yann LeCun began piling into the conversation, with Andreessen calling DeepSeek’s model “one of the most amazing and impressive breakthroughs” he’s ever seen.  

By the end of the weekend, DeepSeek’s AI assistant had rocketed to the top of Apple Inc.’s iPhone download charts and ranked among the top downloads on Google’s Play Store, straining the startup’s systems so much that the service went down for more than an hour. The company was eventually forced to limit signups to those with mainland China telephone numbers — but claimed the move was the result of “large-scale malicious attacks” on its services.

The fallout from the seemingly overnight surge in interest around DeepSeek was swift, and severe: The company’s AI model, which it claims to have developed at a fraction of the cost of rivals without meaningfully sacrificing performance, drove a nearly $1 trillion rout in U.S. and European technology stocks as investors questioned the spending plans of some of America’s biggest companies. The share plunge in AI chipmaker Nvidia Corp. alone erased roughly $279 million in market value, the biggest wipeout in U.S. stock-market history. 

By Monday afternoon, it was clear the overwhelming interest in DeepSeek’s services was taking a toll on the company’s system. “Currently, only registration with a mainland China mobile phone number is supported,” the startup said on its status page. DeepSeek did not specify whether the signup curbs are temporary or how long they will last.

It was the company’s longest major outage since it started reporting its status. Unlike some rivals, DeepSeek’s assistant shows its work and reasoning as it addresses a user’s written query or prompt. Reviews on Apple’s app store and on Alphabet Inc.’s Android Play Store praised that transparency.

Founded by quant fund chief Liang Wenfeng, DeepSeek’s open-sourced AI model is spurring a rethink of the billions of dollars that companies have been spending to stay ahead in the AI race. 

“While it remains to be seen if DeepSeek will prove to be a viable, cheaper alternative in the long term, initial worries are centered on whether U.S. tech giants’ pricing power is being threatened and if their massive AI spending needs re-evaluation,” said Jun Rong Yeap of IG Asia.

Like all other Chinese-made AI models, DeepSeek self-censors on topics deemed politically sensitive in China. Unlike ChatGPT, DeepSeek deflects questions about Tiananmen Square, President Xi Jinping or the possibility of China invading Taiwan. That may prove jarring to international users, who may not have come into direct contact with Chinese chatbots earlier. 

The initial success provides a counterpoint to expectations that the most advanced AI will require increasing amounts of computing power and energy —- an assumption that has driven shares in Nvidia and its suppliers to all-time highs.

The exact cost of development and energy consumption of DeepSeek are not fully documented, but the startup has presented figures that suggest its cost was only a fraction of OpenAI’s latest models. That a small and efficient AI model emerged from China, which has been subject to escalating U.S. trade sanctions on advanced Nvidia chips, is also challenging the effectiveness of such measures.

“The U.S. is great at research and innovation and especially breakthrough, but China is better at engineering,” computer scientist Kai-Fu Lee said earlier this month at the Asian Financial Forum in Hong Kong. “In this day and age, when you have limited compute power and money, you learn how to build things very efficiently.”

For its part, Nvidia — the biggest provider of chips used to train AI software — described DeepSeek’s new model as an “excellent AI advancement” that fully complies with the U.S. government’s restrictions on technology exports. The startup’s work “illustrates how new models can be created” using a technique known as test time scaling, the company said. 

Nvidia’s statement appeared to dismiss some analysts’ and experts’ suspicions that the Chinese startup couldn’t have made the breakthrough it has claimed. The company also pointed out that inference, the work of actually running AI models and using it to process data and make predictions, nonetheless requires a lot of its products.

“Inference requires significant numbers of Nvidia GPUs and high-performance networking,” the company said.

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Accounting

FASB Standardizes Carbon Offsets Accounting Rules

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FASB Standardizes Carbon Offsets Accounting Rules

In a decisive move toward standardized environmental financial reporting, accounting standards boards issued updated implementation guidance during the week ending July 25, 2026, regarding the formal recognition and valuation of corporate carbon offsets and environmental credits. The revised frameworks establish precise rules for how enterprises must measure, record, and disclose carbon credits on balance sheets, eliminating years of inconsistent reporting practices across public capital markets.

Under the finalized accounting standard, purchased carbon offsets can no longer be categorized under vague administrative expenses or unstandardized intangible asset accounts. Instead, organizations must classify environmental credits based on underlying operational intent—distinguishing between credits held for immediate compliance compliance obligations, long-term offset obligations, or active market trading. Furthermore, companies are required to evaluate carbon holdings for fair value impairment at the end of each reporting period, ensuring that depreciated or low-quality environmental credits do not distort corporate asset values.

The standardized rules carry significant implications for corporate audit committees and chief accounting officers. External audit firms are implementing rigorous verification protocols to validate the physical legitimacy, legal ownership, and scientific permanence of carbon credits claimed on balance sheets. Inaccurate or overstated carbon accounting claims now carry substantial financial litigation risk, alongside potential regulatory enforcement for misleading ESG disclosures.

To remain fully compliant, corporate accounting departments must establish centralized carbon tracking systems integrated into primary standard ERP ledgers. Accounting teams that proactively adopt standardized environmental reporting protocols will build investor credibility, streamline annual audit processes, and insulate their organizations against evolving regulatory scrutiny.

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Accounting

Automated Tax Compliance Tools Reduce Risk

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Automated Tax Compliance Tools Reduce Risk

Corporate tax departments reached a critical juncture in automated operational management. With nations worldwide rapidly enacting digital service taxes, localized value-added tax (VAT) mandates, and real-time electronic invoicing requirements, manual tax calculations have become obsolete. Modern corporate tax divisions are aggressively deploying AI-driven tax engine software to automate complex cross-border indirect tax calculations in real time.

The imperative for automated tax compliance stems from the sheer complexity of current trade policies and multi-jurisdictional commerce. E-commerce platforms, software vendors, and global manufacturers face constantly changing regional tax rates, statutory exemption rules, and cross-border tariff structures. Automated tax engines embed directly into enterprise enterprise resource planning (ERP) architectures, automatically applying correct tax codes at the point of sale, calculating real-time withholding amounts, and generating compliant e-invoices.

Automated audit trail generation represents another key advantage of modern tax tech integration. Advanced compliance platforms log every transactional tax determination on immutable digital ledgers, providing tax authorities with transparent, self-verifying audit trails. This capability drastically reduces the operational duration and administrative cost of corporate tax audits, protecting enterprises against severe penalties resulting from calculation errors or missed reporting deadlines.

For chief financial officers and tax directors, investing in automated tax compliance is a vital operational risk mitigation strategy. Automating routine tax calculations frees high-level accounting professionals to focus on strategic tax planning, transfer pricing optimization, and risk management in an increasingly complex global economic environment.

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Accounting

Continuous Auditing Transforms Corporate ERPs

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continuous auditing transforms corporate erps

As corporate accounting departments cross the threshold into late July 2026, the adoption of continuous, automated auditing systems has reached a definitive turning point. Driven by advances in artificial intelligence and deep integration with modern Enterprise Resource Planning (ERP) platforms, leading finance organizations are moving away from traditional, periodic post-hoc audits in favor of real-time, 100% transactional verification. This technological transition is redefining internal control environments, reducing compliance costs, and eliminating the structural delays inherent in legacy quarterly closing processes.

Unlike traditional auditing frameworks that rely on statistical sampling—a process that inevitably leaves operational blind spots—continuous auditing software monitors operational data feeds continuously. Every purchase order, electronic invoice, payroll disbursement, and cross-border wire transfer is automatically cross-referenced against established corporate governance parameters, regulatory tax schedules, and anti-fraud algorithms in real time. Anomalies or unauthorized ledger entries are flagged instantly, allowing internal audit teams to investigate and remediate compliance gaps immediately rather than months after the close of a financial period.

The implications for executive financial management are far-reaching. By embedding continuous verification directly into daily transaction workflows, chief financial officers gain uninterrupted visibility into the organization’s true financial standing. Real-time balance sheet auditing eliminates the severe operational bottlenecks associated with month-end and quarter-end financial reconciliations, freeing accounting professionals to focus on strategic financial modeling, tax planning, and capital allocation rather than manual data entry and spreadsheet consolidation.

However, implementing continuous auditing requires accounting leadership to invest heavily in data governance and technical upskilling. Internal audit teams must evolve from manual ledger reviewers into system architects capable of auditing complex algorithms and validating automated data pipelines. Accounting firms and corporate controllers that master continuous auditing will establish a resilient compliance framework capable of meeting stringent international regulatory standards with total transparency.

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