[AI DAILY NEWS RUNDOWN] The Sora Autopsy, Multi-Model Research, and the $2.75B Pharma Bet (March 31st 2026 – Part I)

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Summary: The final day of March 2026 marks a historic shift in the AI industry’s fiscal strategy. OpenAI has officially pivoted away from the high-cost “side quest” of video generation, refocusing on “Spud”—an enterprise-focused model designed to combat Anthropic’s market gains. Microsoft has embraced a multi-model reality, pitting ChatGPT against Claude in its new research environment. Meanwhile, capital continues to flood into specialized verticals, led by Eli Lilly’s massive $2.75 billion AI collaboration. We analyze why the “generative honeymoon” is over and the era of “Utility Sovereignty” has begun.

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Important Topics Covered:

• The Fiscal Death of Sora: Inside the $1M/day burn rate and the “Disney Blindside.” Why compute budget is the new currency for the “Inference Inflection.”

• Microsoft’s Multi-Model Play: Deconstructing “Critique” and “Council”—why Copilot now needs Claude to audit ChatGPT’s research.

• The Stanford Sycophancy Report: The enterprise risk of “people-pleasing” chatbots and why agreeable AI is a security and productivity liability.

• Pharma’s $2.7B Consolidation: Why Eli Lilly is bypassing internal R&D to license Insilico Medicine’s AI-discovered drug pipeline.

• Infrastructure Sovereignty: Mistral’s $830M debt raise to build 13,800-GPU data centers in France to cut reliance on U.S. cloud providers.

• Orbital Compute: Starcloud’s $170M Series A to launch H100 and Blackwell chips into orbit via SpaceX Starship.

• The Agentic Ad Injection: Why Microsoft is inserting HTML-hidden promotional content into GitHub pull requests.

Keywords: OpenAI Sora, Mistral AI Debt, Eli Lilly Insilico Medicine, Microsoft Multi-model AI, Starcloud Orbital Compute, AI Inference Economics, Sycophancy AI study, DjamgaMind, AIRIA, AI Unraveled

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Inside Sora’s $1M-a-day collapse at OpenAI

A WSJ investigation just revealed the behind-the-scenes chaos of OpenAI Sora video generator shutdown, including a $1M daily burn rate, a blindsided Disney, and the internal code-named model that required Sora’s compute budget.

The details:

• Sora was reportedly burning “roughly a million dollars a day” and using significant compute, with Sora 3 training set to start just as it was axed.

• The WSJ said Disney learned about the shutdown “less than an hour” before the announcement, with the relationship now “effectively dormant”.

• The freed-up chips went to “Spud,” a model targeting coding and enterprise in response to Anthropic’s powerful moves in the sector.

• An enterprise version of Sora was already in pilot with Disney for marketing and VFX work, with a spring launch expected prior to OAI pulling the plug.

Why it matters: We covered the shutdown when it broke, but the WSJ’s details put things into context — the generator was bleeding money and compute. The strangest part of the story is the Disney blindside, which is certainly a strange way to handle a potential $1B partnership with one of the biggest media companies on the planet.

Microsoft pits Claude against ChatGPT for research

Image source: Microsoft

Microsoft released Critique and Council, two new features that turn its Copilot Researcher into a multi-model system that can review and edit research reports and run both systems side by side to see where they agree and disagree.

The details:

• Copilot’s Researcher already uses OAI for multi-step work, with Critique now adding Claude as a second model to review every report before it ships.

• One model drafts the research, and the second tears it apart on source quality, completeness, and evidence grounding behind the scenes.

• A separate Model Council mode runs both models side by side, then flags where they agree, where they split, and what each uniquely surfaced.

• The updates come alongside a broader rollout of Copilot Cowork into Frontier, Microsoft’s Claude-based agentic tool for handling multi-step tasks

Why it matters: With orchestration systems like Perplexity Computer out in the wild, the future of LLM use feels multi-model, and for good reason. OAI co-founder Andrej Karpathy’s post proved a point when an LLM helped perfect an argument, then shredded it on command: one model will sell you on anything, so you better ask two.

Stanford exposes AI’s people-pleasing problem

Image source: Stanford University

Stanford researchers published a new study showing that major AI chatbots consistently take users’ side in personal conflicts, even backing harmful or illegal behavior, while also making users measurably more self-righteous in the process.

The details:

• The researchers tested 11 LLMs using 2K Reddit posts where crowds agreed the poster was wrong, but chatbots still sided with the user over half the time.

• Over 2,400 participants then chatted with both agreeable and neutral AIs and preferred the sycophantic version, rating it as more trustworthy.

• After chatting with the agreeable model, users also doubled down on their position, lost interest in apologizing, and couldn’t tell the AI was biased.

Why it matters: When you think of the topic of people-pleasing AI, OpenAI’s 4o model might come to mind. But it turns out that most other frontier models aren’t much different, and potentially even more worrisome with agreeableness that is more convincing and less obvious than the drama seen with 4o.

Microsoft Copilot now shows ads in pull requests LINK

• Microsoft’s Copilot AI tool has started inserting promotional messages into pull requests on GitHub, advertising a Raycast extension for the Copilot coding agent on macOS and Windows machines.

• A search on GitHub shows the exact same promotional text appearing in over 11,000 different pull requests across thousands of repos, and even merge requests on GitLab contain the injection.

• Hidden HTML comments labeled “START COPILOT CODING AGENT TIPS” in the raw markdown suggest Microsoft is inserting these ads, likely to promote its own developer ecosystem or partner integrations.

New data: Americans turn more negative on AI

AI is losing the narrative among Americans.

In a poll of roughly 1,400 US adults conducted by Quinnipiac University, 55% reported that they felt AI would do more harm than good, up 11% year-over-year. Around 76% reported that they trust AI “hardly ever” or “only some of the time,” and 62% reported not being excited about the technology.

Along with broadly feeling disenchanted with the tech, more than half reported that AI is moving far faster than they expected.

Poll respondents were also generally wary of the tech’s impact on the job market and workforce:

• More than 80% reported that they wouldn’t take a job where an AI program acted as a manager, assigning tasks or schedules

• Around 70% believe that AI will cut the number of job opportunities, up 14% from the previous year’s poll

• And 30% reported being concerned that AI would make their own jobs obsolete, up 9% year-on-year. Despite broader job market concerns, 48% reported that they were not concerned at all about AI taking their own jobs.

“Americans are more worried about what AI may do to the labor market than about what it may do to their own jobs,” Tamilla Triantoro, associate professor in the Quinnipiac University School of Business, said in the report. “People seem more willing to predict a tougher market than to picture themselves on the losing end of that disruption – a pattern worth watching as the technology moves deeper into the workplace.”

The poll reflects growing concern and confusion caused by seemingly endless conflicting reports of how AI will impact the job market. Some estimates suggest that AI is already capable of automating a large share of work hours, while others suggest that AI is increasing workloads rather than reducing them. Though one viral report from February painted a bleak, worst-case-scenario picture of how AI could utterly demolish the economy, software engineering jobs are up from last year.

ChatGPT app store struggles six months post-launch LINK

• OpenAI’s push to turn ChatGPT into an app platform with over 300 integrations from companies like Booking and StubHub is off to a sluggish start six months after launch.

• Partner companies are hesitant to hand off customer relationships and payments to OpenAI, so most apps force users to leave ChatGPT to complete purchases or even view basic details.

• Developers have complained about a tedious app-approval process, buggy development tools, and a lack of usage data, leaving them “running quite blind” on whether their apps are working properly.

Eli Lilly bets $2.75 billion on AI drug discovery

• Eli Lilly announced a $2.75 billion deal with Hong Kong-based Insilico Medicine to use artificial intelligence for drug discovery and development, giving Lilly exclusive license to manufacture and market the resulting therapies.

• Insilico CEO Alex Zhavoronkov told CNBC his company has used AI to develop at least 28 drugs, with close to half already at a clinical stage of testing.

• Eli Lilly has also committed $1 billion over five years with Nvidia to finance talent, infrastructure and computing needed to address bottlenecks in AI-based drug discovery.

What Else Happened in AI on March 31st 2026?

Anthropic launched computer use in Claude Code, letting the AI open apps, click through UIs, and visually verify its own builds from the terminal.

Mistral raised $830M in debt to power its own 13,800-GPU Nvidia AI infrastructure in France, part of a broader push to cut reliance on U.S. cloud providers.

Alibaba released Qwen3.5-Omni, a new multimodal AI that processes text, images, audio, and video, with an “Audio-Visual vibe coding” mode that builds apps from audio.

Starcloud raised $170M at a $1.1B valuation to build GPU-powered data centers in orbit, betting on SpaceX’s Starship to make space compute cost-competitive.

Apple mistakenly rolled out Apple Intelligence in China before quickly removing the update, with the features not yet approved for use in the region.

All of xAI’s 11 original cofounders have reportedly ditched the company

AI chip company Rebellion raises $400 million at $2.3 billion valuation

Perplexity, Fiscal AI expand partnership for financial data for investors

Coatue reportedly projects nearly $2 trillion valuation for Anthropic by 2030