Top AI & Tech News (Through October 5th)

Hello AI Citizens 🤖,

This week’s theme is beating “workslop”: polished-looking AI output that shifts the real work to someone else. CAIOs can turn AI from a content machine into a results engine by setting clear quality bars and keeping humans accountable for outcomes. Require every AI-assisted deliverable to include the brief, sources, assumptions, and acceptance criteria, and default to human edits over blind automation. Add guardrails in daily tools (auto checks for citations, facts, and duplication) and track rework minutes, first-pass acceptance, cycle time, and downstream satisfaction. Teach better prompting and a quick “slop sniff test,” and require structured reviewer feedback so AI becomes a force multiplier, not more inbox mess.

Here are the key headlines shaping the AI & tech landscape:

• Sora 2 Launches: Physics-Aware, Controllable Video + Audio (and a Social App)

• Meta to Acquire RISC-V Chip Startup Rivos to Supercharge Meta Training & Inference Accelerator (MTIA) program

• AI ‘Actress’ Tilly Norwood Debuts as Studios Quietly Advance Synthetic Talent

• HBR: “Workslop” Low-Effort AI Output Is Costing over $9M/year in a 10,000-person Organisation

• Periodic Labs Raises $300M Seed to Build AI Scientists

• Meta to Use AI Chat Interactions to Personalize Content and Ads Starting Dec 16

Let’s recap!

Sora 2 Launches: Physics-Aware, Controllable Video + Audio (and a Social App)

OpenAI released Sora 2, a video/audio generation model with big jumps in physical realism (e.g., true rebounds, buoyancy) and multi-shot controllability, including synced dialogue and sound effects. It can persist world state and insert real people/objects via “cameos.” OpenAI also launched an invite-based Sora iOS app (U.S./Canada first) with consent/parental controls; Sora 2 Pro on web and an API are planned. Initial access is free with usage limits due to compute. Source: OpenAI (Sept 30, 2025).

💡 : Treat Sora 2 as both a creation tool and a simulation engine. Pilot it for marketing storyboards, training content, UX prototyping, and synthetic data. Wrap use in guardrails: explicit likeness/voice consent, provenance labels (e.g., C2PA), no-train clauses on your content, and human QA before publishing plus policies for teen/consumer scenarios and a budget for burst compute.

Meta to Acquire RISC-V Chip Startup Rivos to Supercharge Meta Training & Inference Accelerator (MTIA) program

Meta said it plans to buy Santa Clara–based Rivos, a RISC-V chip startup, to accelerate its custom Meta Training & Inference Accelerator (MTIA) program. Terms weren’t disclosed; Reuters notes Rivos had been nearing a ~$2B funding round and that Meta has been a major customer. Meta says Rivos brings “full-stack AI systems” expertise, complementing its heavy near-term reliance on Nvidia while pushing down long-run infrastructure costs. The move underscores big tech’s shift to in-house silicon to control performance, cost, and power at scale. Source: Reuters (Sept 30, 2025).

💡Plan a two-track compute strategy: secure near-term GPU capacity while building portability to custom/alt-ISA accelerators (e.g., RISC-V) via ONNX/TVM/IREE and PyTorch compile paths. Negotiate contracts for code portability and kernel access, and stand up a small “silicon PMO” to benchmark TCO (perf/W, latency, memory BW) across hardware. Update DPAs/export-control reviews for new chips, and invest in firmware/compilers talent so your models can follow the cheapest, fastest silicon without lock-in.

AI ‘Actress’ Tilly Norwood Debuts as Studios Quietly Advance Synthetic Talent

At Zurich Summit, producer Eline Van der Velden introduced Tilly Norwood—an AI-generated “actress” from her studio Xicoia (a Particle6 spin-off)—saying multiple talent agencies are circling and a rep announcement is coming. Norwood has already “appeared” in a comedy sketch (“AI Commissioner”), and Van der Velden claims studios that were skeptical in February were eager by May. The ambition: position Tilly “like the next Scarlett Johansson or Natalie Portman,” arguing audiences prioritize story over whether a star “has a pulse.” The pitch taps cost pressure and creative flexibility, but comments and coverage show sharp backlash over consent, soulfulness, and labor impact. Source: Variety (Sept 28, 2025).

💡 If your company makes media or marketing, assume synthetic performers will enter your supply chain and set guardrails now. Require explicit, revocable consent for any real person’s likeness/voice, disclose AI use to viewers, and embed provenance (e.g., C2PA) and watermarks in all outputs. Update talent contracts and vendor DPAs to ban training on unconsented materials, define reuse limits, and set residual/royalty rules; add legal/ethics review for intimacy or sensitive scenes. Stand up a “synthetic talent register” with approvals, audit logs, and brand-safety checks so creative speed doesn’t outpace reputation and regulatory risk.

HBR: “Workslop” Low-Effort AI Output Is Costing over $9M/year in a 10,000-person Organisation

Harvard Business Review flags a growing problem: AI-generated, polished-looking content that lacks substance is flooding workflows and forcing coworkers to fix it. In a survey of 1,150 U.S. full-time employees, 40% said they received “workslop” in the past month, estimating ~15% of incoming content fits the bill; each incident takes ~1 hour 56 minutes to unwind and costs about $186 per employee per month—over $9M/year in a 10,000-person org. Beyond time loss, recipients downgrade senders’ perceived creativity, reliability, and trustworthiness, risking team cohesion and AI adoption. The authors tie the surge to indiscriminate “use AI everywhere” mandates and urge clearer norms. Source: Harvard Business Review (Sept 22, 2025; updated Sept 25, 2025).

💡 Replace “use AI” mandates with “use AI well” rules: define where AI is appropriate, require an owner-of-record, inputs/citations, and a quick quality checklist before sharing. Ban raw copy-paste; make human review and “why this is useful” summaries standard, and coach teams on prompt craft and editing. Track rework/rejection rates and cycle time, and deploy an internal “workslop detector” to flag generic filler so feedback loops improve output quality instead of spreading busywork.

Periodic Labs Raises $300M Seed to Build AI Scientists

Periodic Labs emerged from stealth with a $300M seed to build “AI scientists”: autonomous labs where robots run experiments, learn, and iterate. Founded by former DeepMind/Google Brain researcher Ekin Dogus Cubuk (GNoME) and ex-OpenAI research VP Liam Fedus (early ChatGPT, trillion-parameter models), the startup’s first target is new superconductors, with a broader push to generate proprietary physical-world data for model training. Backers include a16z, DST, Nvidia, Accel, Elad Gil, Jeff Dean, Eric Schmidt, and Jeff Bezos, reflecting surging investor interest in automated materials discovery. Source: TechCrunch (Sept 30, 2025).

💡If you have wet labs or advanced R&D, start piloting “self-driving lab” loops now—connect ELN/LIMS, robotics, and modeling so hypotheses auto-trigger experiments with human checkpoints. Make data rights the centerpiece of any partnership (who owns raw logs, derived datasets, and model improvements), and set KPIs like experiments/day, cost per hypothesis, reproducibility, and time-to-insight. Stand up safety & compliance rails early (chemical handling, biosafety, audit logs), and negotiate compute/robotics capacity ahead of demand to avoid bottlenecks.

Meta to Use AI Chat Interactions to Personalize Content and Ads Starting Dec 16

Meta will start folding what people say to its Meta AI (voice or text) into the signals that shape feed, Reels, and ad recommendations across Facebook and Instagram—without an opt-out for those who use Meta AI. Sensitive topics (e.g., health, religion, politics, sexual orientation, race/ethnicity) won’t be used for ads, and the rollout begins Dec 16 in most regions, excluding the UK, EU, and South Korea. Notifications go out Oct 7; Meta AI now counts 1B monthly users, and the move leans into CEO Mark Zuckerberg’s push for a more personalized, voice-first assistant experience. Source: Reuters (Oct 1, 2025).

💡If your product uses conversational AI, treat chat logs like ad-targeting data: update privacy notices, turn on region-aware controls (opt-in in strict jurisdictions), and set clear retention/minimization rules. Build “sensitive topic” filters, offer an easy “don’t use my chats for personalization” toggle, and A/B test lift with holdouts to prove value—while logging every decision for auditability.

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