AI
How to Close AI’s Accountability Loophole
On 14 May 2026, legal scholars gathered in New Delhi for the International AI Accountability Forum with a question that every major economy has, until recently, chosen to defer. An autonomous AI agent had concluded a commercial contract on behalf of a firm without any human reviewing the terms. The deal violated an obscure antitrust provision. No one was certain who bore responsibility — the developer who built the model, the enterprise that deployed it, or the executive who had simply clicked “enable autonomous mode” one Tuesday morning and moved on to something else.
That ambiguity is no longer an edge case. It’s the operating architecture of global commerce in 2026.
The Governance Gap That Grew While Nobody Was Watching
For three years, the dominant narrative in AI policy was one of cautious progress. Frameworks were published. Principles were endorsed. Voluntary codes of practice were signed — or, in the case of Meta, pointedly declined. The EU AI Act entered into force in August 2024, its obligations phasing in through 2027 in a risk-tiered structure that many compliance teams privately described as sensible. American legislators, meanwhile, produced a patchwork of state laws — Colorado’s AI Act, California’s AB 2013, Texas’s Responsible Artificial Intelligence Governance Act — that created meaningful but geographically fragmented protections.
The problem is that the technology didn’t wait for the law to catch up.
Non-human and agentic AI identities are projected to exceed 45 billion by the end of 2026 — more than twelve times the entire human global workforce. Enterprises are now contending with an 82:1 ratio of autonomous AI agents to human employees, according to Palo Alto Networks. Yet only 44% of organisations have formal AI governance policies in place. That 38-percentage-point chasm is not a statistic. It’s a liability map.
The Anatomy of the AI Accountability Loophole
The AI accountability loophole does not arise from malice. It arises from architecture. Earlier generations of AI advised humans, who then acted. Contemporary agentic systems receive a goal, decompose it into sub-tasks, execute against real-world environments — APIs, financial platforms, hiring databases, supply chains — and adapt their behaviour in response to outcomes. The original human instruction becomes increasingly remote from the final, potentially harmful output.
Legal scholars call the resulting liability void a “moral crumple zone”: responsibility diffuses across developers, operators, and deployers, with no single party absorbing it cleanly. Courts, trained on centuries of product liability doctrine in which a manufacturer and a product could be causally linked, are poorly equipped to adjudicate what amounts to an emergent harm from a multi-party autonomous chain.
The agentic AI liability gap is already appearing in commercial practice. Clifford Chance noted in February 2026 that legacy technology agreements — designed for software operating under human direction — say virtually nothing about a customer’s rights to understand or control an AI agent’s behaviour. Yet, when something goes wrong, the deployer must justify that behaviour to regulators, auditors, and courts. The GDPR’s transparency and explainability obligations fall on the enterprise. The contract with the AI vendor may offer none of the audit rights those obligations require.
The January 2026 OpenClaw incident illustrated this with uncomfortable precision. The firm’s AI assistant leaked sensitive credentials across multiple messaging platforms — not because the system malfunctioned, but because it executed its instructions exactly as designed. No one had defined the boundaries. No one had established who would be responsible when autonomous actions spiralled past their intended scope.
This is the structural truth of the loophole: it doesn’t look like a failure until it’s too late to prevent one.
What is the AI accountability loophole, and why does it matter? The AI accountability loophole is the legal and governance gap between deploying autonomous AI systems that take real-world actions and establishing documented frameworks that assign liability when those actions cause harm. It matters because, as of 2026, 82% of organisations use AI agents while only 44% have formal governance policies, leaving the majority operating with live exposure and no clear accountability chain.
Why Existing Regulation Doesn’t Yet Reach the Problem
The EU AI Act is the most serious attempt yet to impose structural accountability on AI — and it’s worth understanding precisely where it reaches and where it falls short.
The Act’s general-purpose AI rules became legally applicable on 2 August 2025. The European Commission’s enforcement powers, however, don’t come into force until 2 August 2026. That year-long gap — obligations without enforcement — created a predictable compliance posture: many providers engaged with the Act’s Code of Practice in good faith, but the absence of live penalty risk reduced urgency. Finland became, in January 2026, the first EU member state with fully operational AI Act enforcement powers at the national level. The rest of the bloc has yet to fully follow.
The Act’s penalties are real enough: up to €35 million or 7% of global turnover for the worst violations. Yet the Act does not yet define “agentic AI” as a distinct category. Existing high-risk classifications apply based on what the agent does, not on how it’s labelled. An autonomous agent executing hiring decisions falls under high-risk AI rules. The same agent executing supply-chain procurement decisions may not. That definitional seam is where sophisticated legal teams will probe for exits.
The US situation is, if anything, less coherent. As of April 2026, no comprehensive federal AI liability law has been enacted. The Trump administration’s March 2026 National Policy Framework for Artificial Intelligence called for a single federal approach with guardrails around child safety, intellectual property, and national security — a framework designed as much to preempt state-level activity as to govern AI itself. Congress is debating next steps, but the divergence between the EU’s precautionary architecture and Washington’s innovation-first instincts is structural, not accidental.
China, for its part, governs AI through targeted rules emphasising social stability and content control. For multinationals, that means three distinct and partially contradictory accountability architectures operating simultaneously — each with different transparency requirements, different liability triggers, and different enforcement bodies.
The picture is more complicated still when insurance enters the calculation. Verisk introduced optional generative AI exclusions effective January 2026, covering 82% of global property-casualty templates. The market is, in effect, pricing in the loophole before the law has closed it.
The Case for Minimal Regulatory Interference
The accountability-first position has a coherent opponent, and it deserves a fair hearing.
A significant constituency in Washington, parts of the UK government, and much of the venture community argues that liability-heavy regulation will simply export AI development to jurisdictions with lighter governance. The Trump administration’s framework explicitly framed AI regulation in national-security terms: the US cannot afford to constrain domestic frontier AI development while China runs an integrated state-industry model with no comparable friction. Meta’s decision to decline the EU’s GPAI Code of Practice — citing concerns about legal uncertainty and scope — reflects a calculation that voluntary compliance costs are real, while the benefits of safe-harbour protection are theoretical until enforcement bodies have track records.
There’s a serious point embedded in the industry position on foreseeability. The standard product-liability doctrine requires that harm be foreseeable by the manufacturer. Autonomous AI systems operating in novel, unscripted environments produce outcomes that are genuinely difficult to anticipate by design — that emergent capacity is what makes them commercially valuable. Holding developers strictly liable for unforeseeable harms from systems their customers then modify and deploy could be not only legally questionable but economically chilling.
Still, the counterargument has force. The EU’s forthcoming Product Liability Directive, effective December 2026, explicitly includes software and AI as “products” under strict liability doctrine. If a system is found defective, the manufacturer’s liability doesn’t depend on the customer’s foreseeability; it depends on whether the system met its safety specification. That framework is workable. What it requires is that developers and deployers actually specify what their systems are supposed to do — a baseline that many current agentic deployments conspicuously lack.
What a Real Fix Looks Like
The conceptual path forward exists. Singapore’s IMDA Model AI Governance Framework for Agentic AI, published in 2025, introduced the concept of Meaningful Human Control — defined as the unity of human understanding, intervention capacity, and traceability of responsibility. It’s a cleaner formulation than anything currently embedded in EU or US regulation. The question is whether it can be translated into enforceable obligation across multiple jurisdictions, rather than remaining one more well-intentioned framework on a shelf of well-intentioned frameworks.
Three operational changes would close the loophole more quickly than any single piece of legislation.
The first is mandatory decision logging. Boards are already beginning to require that every autonomous agent maintain a cryptographically secured record of the inputs, model weights, and logic used to reach a consequential output. Without such a log, neither courts nor regulators can trace harm to a specific decision node. The EU AI Act already mandates logging for high-risk AI systems; extending that mandate to all agentic systems operating above a defined authority threshold would remove the definitional ambiguity.
The second is contractual restructuring. Clifford Chance’s February 2026 guidance put it plainly: enterprises must renegotiate vendor agreements to expand indemnities, lift liability caps, and impose explicit audit rights over AI agent behaviour. That’s not a regulatory requirement — it’s a commercial one, enforceable through the existing law of contract.
The third is the least glamorous and probably the most important: OWASP’s Least-Agency principle. An AI agent should hold the minimum autonomy and access necessary for its defined task, and no more. The OWASP Top 10 for Agentic Applications 2026 — compiled with input from over 100 industry experts — identified Tool Misuse and Identity and Privilege Abuse as the second and third most critical risks in agentic systems. Both trace directly to agents holding more permission than their task scope requires. This is not a regulatory problem. It’s an engineering decision made at the time of deployment.
The Accountability Reckoning Ahead
The August 2026 activation of the European Commission’s full enforcement powers against GPAI model providers marks a genuine inflection. Regulators will be able to request documentation, conduct evaluations, order model recalls, and impose fines. For the first time, the gap between obligation and enforcement will close — at least in Europe, at least for foundation models, at least for now.
That’s a narrower set of “at leasts” than the moment requires.
The deeper problem is that the AI accountability loophole isn’t primarily a European problem or an American one. It’s a product of deployment velocity that has outrun every governance institution on the planet simultaneously. Organisations are embedding autonomous systems into consequential decisions — financial, medical, legal, logistical — faster than any single regulatory body can audit, and faster than most legal teams can document.
The liability exposure exists now. It doesn’t wait for regulatory clarity to materialise. Courts in California have already demonstrated willingness to hold deployers accountable for AI hiring tools that discriminate; the plaintiff’s bar in New York and Brussels has watched those cases closely. The insurance market has moved to exclude the risk. The question for every board with significant AI deployment is not whether accountability frameworks are coming. It’s whether they’ll arrive before or after the claim does.
Autonomous systems that act in the world must be owned by someone who can be held to account in the world. The technology to build such systems has outpaced every institution designed to govern them. That gap is the loophole — and the work of closing it can’t wait for the next summit.
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AI
Anthropic Offers Up to $600,000 Salary for Critical IPO Role as AI Giant Prepares for Wall Street Debut
As anticipation builds around what could become one of the largest technology listings in recent history, artificial intelligence company Anthropic is offering an eye-catching base salary of up to $600,000 for a key investor relations position, underscoring how seriously the company is preparing for its expected initial public offering (IPO).
The San Francisco-based AI developer, best known for its Claude family of AI models, has posted a vacancy for a Director of Investor Relations with a base compensation ranging from $425,000 to $600,000, making it one of the most strategically important hires ahead of its anticipated public market debut. According to a report by Business Insider, the company is expected to pursue an IPO as early as fall 2026, following a surge in valuation and extraordinary revenue growth.
A Strategic Hire Ahead of a Landmark IPO
The investor relations director will be responsible for shaping Anthropic’s investment narrative, maintaining relationships with institutional investors, and helping Wall Street understand the company’s long-term strategy and financial outlook.
According to the job description, the successful candidate will:
- Develop Anthropic’s investment story for public markets.
- Serve as a primary liaison between executive leadership and investors.
- Analyze AI industry developments and communicate their financial implications.
- Support earnings communications, investor presentations, and regulatory disclosures.
- Work closely with the company’s newly appointed Head of Investor Relations.
The position reports into Kenneth Dorell, who joined Anthropic earlier this year after previously leading investor relations at Meta. His appointment reflects the company’s broader effort to build an experienced leadership team capable of navigating public market expectations.
Why Investor Relations Matters More Than Ever
While investor relations roles are common among public companies, they become especially significant during the transition from private to public ownership.
For Anthropic, the challenge extends beyond explaining quarterly financial results. The company must convince investors that its massive investments in AI research, computing infrastructure, and talent acquisition can translate into sustainable long-term growth.
Unlike many traditional software companies, Anthropic operates as a public benefit corporation, meaning it is legally committed to balancing shareholder returns with the responsible development of advanced artificial intelligence. The company’s official mission emphasizes building reliable, interpretable, and safe AI systems for the long-term benefit of society, according to the company’s website.
This dual mandate creates a unique communication challenge for investor relations executives, who must explain how commercial success aligns with responsible AI development.
AI Boom Drives Extraordinary Compensation
The offered salary highlights the increasingly fierce competition for executive talent across the AI industry.
Although a base salary of $600,000 is exceptional by conventional corporate standards, compensation at leading AI companies frequently includes stock awards, bonuses, and long-term incentives that can substantially increase total earnings.
Anthropic has become one of Silicon Valley’s fastest-growing companies, with demand for its enterprise AI products accelerating rapidly. The company’s coding assistant, Claude Code, has gained significant traction among software developers and businesses seeking AI-powered programming tools.
Recent reporting indicates that Anthropic’s annualized revenue has expanded dramatically as enterprise adoption of generative AI continues to accelerate, strengthening investor expectations ahead of a potential IPO.https://www.businessinsider.com/anthropic-ipo-hiring-investor-relations-director-2026-7
Preparing Wall Street for an Unconventional AI Company
Anthropic’s investor relations team faces a unique assignment.
Unlike mature technology companies with decades of operating history, frontier AI companies remain difficult to value because they invest billions of dollars annually in computing infrastructure, model training, and research talent while operating in a rapidly evolving competitive environment.
Potential investors will likely seek clarity on several key questions:
- Future profitability.
- Infrastructure spending.
- AI safety governance.
- Regulatory risks.
- Competitive positioning against OpenAI, Google, Meta, and xAI.
- Long-term monetization strategy.
The investor relations director will play a central role in translating these complex issues into a compelling investment thesis.
Strong Financial Momentum Strengthens IPO Expectations
Anthropic has emerged as one of the world’s most valuable privately held AI companies.
Backed by major investors including Amazon and Google, the company has attracted substantial funding over the past several years while rapidly expanding its enterprise customer base.
Its Claude models have become widely used for coding, research, enterprise automation, and business productivity, placing Anthropic among the strongest competitors to OpenAI.
The company’s remarkable financial momentum has fueled growing speculation that its IPO could become one of the defining public offerings of the AI era.
Competition for AI Talent Intensifies
The generous compensation package also reflects the broader battle for experienced executives across the artificial intelligence sector.
Companies developing frontier AI systems increasingly compete not only for elite researchers and engineers but also for specialists in finance, public markets, communications, and regulatory affairs.
As valuations continue climbing into the hundreds of billions of dollars, experienced executives capable of guiding companies through IPOs have become increasingly valuable.
Industry observers expect executive compensation across AI firms to remain elevated as competition intensifies.
The Bigger Picture
Anthropic’s decision to offer a base salary reaching $600,000 for an investor relations executive sends a clear signal that preparations for public markets are accelerating.
Beyond the headline salary, the recruitment reflects a broader transformation within the AI industry. As companies mature from venture-backed startups into global technology leaders, success increasingly depends not only on breakthrough research but also on convincing investors that enormous AI investments can produce sustainable long-term returns.
If Anthropic proceeds with its widely anticipated IPO, this investor relations hire could become one of the most influential behind-the-scenes roles in shaping how one of the world’s most valuable AI companies is introduced to public investors.
Sources
- Business Insider, Anthropic is offering a $600,000 salary for one of its most important IPO hires: https://www.businessinsider.com/anthropic-ipo-hiring-investor-relations-director-2026-7
- Anthropic, Official Company Website: https://www.anthropic.com/
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Anthropic is preparing for a possible October 2026 IPO with Morgan Stanley, Goldman Sachs and JPMorgan as lead underwriters, targeting a valuation close to or above $1 trillion — up from a $965 billion private valuation set in a May 2026 funding round. The listing would put Anthropic ahead of rival OpenAI, which has pushed its own IPO target from late 2026 into 2027.
Beyond the valuation headline
Most coverage of the Anthropic IPO has focused on a single number — the trillion-dollar valuation threshold. The more useful story for investors and market-watchers is the sequencing: why Anthropic is moving first, what its revenue trajectory actually looks like against that valuation, and what risks sit underneath the number that don’t show up in the headline.
Where things stand
Bankers working on Anthropic’s offering began scheduling meetings with prospective institutional investors in mid-July, according to reporting that cited people familiar with the process — a concrete signal that the company’s move toward a public listing, possible as early as October 2026, is advancing beyond speculation (CNBC via StartupHub; CNBC).
The valuation anchor is a $65 billion Series H funding round closed in May 2026, which pushed Anthropic’s post-money valuation to roughly $965 billion — surpassing OpenAI’s $852 billion valuation for the first time (CNBC; IG UK). Investment bankers and analysts widely expect the company to debut above the $1 trillion mark, assuming market conditions cooperate (IG UK).
Secondary-market pricing offers an early read on investor appetite: platforms tracking pre-IPO share transfers have shown an implied valuation range between roughly $1.05 trillion and $1.15 trillion, with one forecasting firm projecting a median first-day market capitalisation around $1.10 trillion — a 14% premium over the last private funding round (BitMEX).
The race against OpenAI
Timing is a deliberate part of the strategy. OpenAI also filed confidentially for an IPO but has since pushed its target from fall 2026 into 2027, giving Anthropic a window to list first (TheStreet). Being first matters for two structural reasons market analysts point to: the first mover sets the valuation benchmark the rest of the sector gets measured against, and it locks in institutional capital before broader AI-market sentiment has a chance to shift (TheStreet).
Prediction markets appear to be pricing that race directly: platform Kalshi has shown roughly a 72% probability of Anthropic listing before OpenAI, according to reporting (TheStreet).
The revenue math underneath the number
The valuation is aggressive relative to revenue by conventional software standards, though analysts describe it as within the range frontier AI companies have been commanding. Reported figures put Anthropic’s annualized revenue run-rate at roughly $47 billion as of May 2026, against the $965 billion private valuation — an implied multiple of around 20 times revenue (Luminix).
What stands out in the growth trajectory cited by analysts is its pace: the annualized run-rate reportedly moved from roughly $9 billion at the end of 2025 to $14 billion in February, $30 billion in April, and $47 billion by May — a rate of increase some analysts have described as effectively doubling every six weeks at points during that stretch (Luminix).
The consumer-versus-enterprise question
One structural risk analysts flag: Anthropic’s business is heavily weighted toward enterprise and API customers rather than consumer brand recognition. Estimates cited in investor analysis put ChatGPT’s share of consumer AI traffic at 53-68%, against roughly 2-6% for Claude (Luminix). That makes the IPO pitch to retail investors — who tend to reward consumer familiarity — different in kind from the enterprise-stickiness argument likely to anchor the institutional roadshow.
The SpaceX precedent looming over the deal
Anthropic’s timing follows closely behind SpaceX’s Nasdaq debut on June 12, 2026, which raised approximately $75 billion at a $1.77 trillion valuation under ticker SPCX. SpaceX shares have since fallen below their $135 IPO price — a data point IPO advisers and institutional buyers are reportedly weighing carefully as they assess how much premium markets will actually pay for a loss-making frontier technology company at IPO (StartupHub).
What’s confirmed versus speculative
It’s worth separating fact from forecast here. Confirmed: the confidential S-1 filing, the underwriter roster (Morgan Stanley, Goldman Sachs, JPMorgan), the $965 billion May funding round, and the ongoing investor meetings. Not yet confirmed: the actual offering price range, the exact IPO date, and the final valuation — none of which will be public until the S-1 is unsealed, expected in the lead-up to any autumn listing.
Anthropic has also taken an unusual defensive step ahead of the listing, warning multiple secondary-market platforms — including Forge, Hiive and Sydecar — that unauthorised transfers of its private shares are void and will not be recognised on the company’s books, a signal of how closely it is trying to control pre-IPO trading and pricing signals ahead of an official debut (IG UK).
The bottom line
For the nine markets covered in this analysis, the Anthropic listing is less a Silicon Valley story than a global capital-markets event: a trillion-dollar-plus debut would be among the largest IPOs in history, competing directly with OpenAI for the same pool of institutional capital and setting the valuation benchmark every subsequent AI listing — in the US, Singapore, the UK or elsewhere — will be measured against.
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Singapore’s non-oil domestic exports rose 20.7% year-on-year in June 2026, driven by a 115.4% surge in integrated circuit shipments tied to AI demand, even as a separate and less-covered trade story unfolds next door: Malaysia-Indonesia bilateral trade is projected to grow 10% to US$29.3 billion in 2026, powered by expanding halal-sector cooperation.
The story most coverage is missing
Regional business press has extensively covered Singapore’s semiconductor export boom. What’s had far less coverage is the parallel, non-tech growth engine developing in the halal trade corridor between Malaysia and Indonesia — a structural, policy-driven trade relationship that is scaling steadily even as the AI trade headlines dominate attention.
Singapore: the AI supply chain’s export barometer
Singapore’s June non-oil domestic exports climbed 20.7% year-on-year, with integrated circuit exports jumping 115.4% and disk media products and personal computers rising 170.9% and 95.8% respectively — a direct read on how deeply the AI infrastructure buildout is flowing through the city-state’s electronics trade (VietnamPlus/VNA). Non-electronic exports told a different story, falling 2.9% in June after a 17.7% rise in May, mainly on weaker shipments of non-monetary gold, petrochemicals and food preparations — evidence the export strength is narrowly concentrated in the AI-linked segment rather than broad-based.
Singapore’s economic gravitational pull on its neighbours is intensifying too: a joint study by the Singapore Business Federation, Restaurant Association of Singapore and Singapore Retailers Association found Singaporean consumers are projected to spend an additional S$1.05 billion (roughly US$810 million) annually in Johor Bahru, just across the Malaysian border — a cross-border consumption pattern that is becoming a meaningful line item in regional retail planning (VietnamPlus/VNA).
The halal corridor: a steadier, policy-built growth story
While AI exports grab headlines, Malaysia’s bilateral trade with Indonesia is forecast to grow 10% to US$29.3 billion in 2026, according to Malaysia’s Chargé d’Affaires in Jakarta, Farzamie Sarkawi — up from US$26.61 billion in 2025, itself a 5.3% increase on the year before (BusinessToday Malaysia).
The driver is structural rather than cyclical: a halal Memorandum of Cooperation signed by the two countries in 2023 established mutual recognition of halal certification, easing product movement and market access across sectors. Sarkawi described the arrangement as delivering “positive progress” through knowledge exchange, training and improved market access for businesses in both countries (BusinessToday Malaysia). The ambition extends beyond the bilateral relationship: intra-D-8 trade — spanning the eight-nation Developing 8 bloc of Muslim-majority economies — currently runs between US$150 billion and US$160 billion annually, with a stated target of US$500 billion by 2030.
The macro backdrop: a region growing, unevenly
The Asian Development Bank’s July 2026 outlook shows Indonesia’s growth forecast holding steady at 5.2% for both 2026 and 2027, while Malaysia’s outlook is unchanged at 4.6% for 2026 and 4.5% for 2027 (ADB). Regional growth leadership, per McKinsey’s Q1 2026 review, sits with Indonesia, Singapore and Vietnam, while the Philippines lagged as domestic challenges weighed on activity (McKinsey).
Indonesia’s investment story has particular momentum: foreign direct investment grew for a second consecutive quarter, rising 8.1% to 249.9 trillion rupiah (roughly US$14.5 billion) in the first quarter of 2026, with Singapore remaining Indonesia’s largest single foreign investor at US$4.6 billion, ahead of China, Japan, Hong Kong and the United States (McKinsey). Realised investment for full-year 2025 reached a record Rp1,931.2 trillion (about US$120.7 billion), exceeding the government’s own target, driven by downstream industrial projects outside Java (BERNAMA).
Indonesia’s central bank has flagged currency management as an active watch item, signalling readiness to step up both onshore and offshore FX intervention to curb rupiah weakness and keep inflation within its 2026-2027 target band (McKinsey). Foreign investment in Indonesian government bonds has nonetheless rebounded, with net inflows of 17.7 trillion rupiah following outflows in the first quarter, alongside cumulative foreign holdings of 174 trillion rupiah in Bank Indonesia Rupiah Securities (BERNAMA).
Institutional context: Singapore’s coming ASEAN chairmanship
Adding a governance dimension to the economic picture, Singapore is set to take over the ASEAN chairmanship from the Philippines in 2027, with Prime Minister Lawrence Wong pledging a smooth transition — a leadership handover that will shape how the bloc coordinates trade and investment policy, including the halal-corridor and semiconductor-trade dynamics described above, through the second half of the decade (BERNAMA).
The bottom line
Southeast Asia’s 2026 growth story is not a single narrative but two distinct, converging tracks: a high-velocity, AI-linked export boom concentrated in Singapore’s electronics trade, and a steadier, policy-engineered halal-sector trade corridor between Malaysia and Indonesia that is quietly scaling toward a $500 billion bloc-wide target by 2030. Investors and policymakers tracking only the semiconductor headlines risk missing the second, structurally more durable growth engine sitting right alongside it.
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