Is Neko Health’s body scan worth it? Spotify billionaire’s startup has come to America

techcrunch.com Oct 1, 2026

Is Neko Health’s body scan worth it? Spotify billionaire’s startup has come to America

Curated by Shubham · TechCapsules · Oct 1, 2026

AI-summarised brief · reviewed before publication

Spotify founder Daniel Ek’s startup Neko Health secured $700 million to develop a consumer body‑scan platform aimed at preventative health. The company competes with rivals such as Midjourney and Function Health, all seeking to embed body scanning into mainstream healthcare. TechCrunch’s Equity podcast features investor Farooq Abbasi discussing Neko’s strategy, funding dynamics, and the broader market potential for body‑scanning technology. The episode highlights investor enthusiasm and the challenges of integrating new diagnostics into existing medical systems.

💡 Why It Matters

· The surge in body‑scan startups signals a shift toward data‑driven prevention, potentially redefining early disease detection and patient engagement.

Read full article on techcrunch.com

How AI is becoming Hollywood’s newest star, changing work on and off…

When “Hell Grind” premiered at Cannes, it drew attention not for star power but for being fully generated by artificial intelligence. The 95‑minute action film was produced by Higgsfield AI, a startup of 15 people, in under three weeks on a $500,000 budget, with 80 % of costs allocated to compute power. All actors, visuals and effects were AI‑created, though the company’s co‑founder Mahi De Silva stresses that directors, writers and designers will remain essential. Higgsfield AI’s platform, Cinema Studio, integrates 33 AI models such as OpenAI’s ImageGPT and Google’s Nano Banana. The startup raised $400 million in a Series B round, valuing it at $5.4 billion, and is testing licensed human likenesses for future projects.

💡 AI‑driven production could slash traditional filmmaking costs while reshaping creative labor dynamics.

finimize.com · Oct 1

CScale Raised $145 Million To Bring Optics Closer To AI Chips

Silicon Valley startup CScale, backed by Nvidia and Intel, announced a $145 million financing round led by Atreides Management, Valor Equity Partners and Premji Invest, bringing total capital to $188 million. The company says its technology can embed tiny lasers directly onto AI chips and preserve data flow when a laser fails, turning a potential outage into a reduced‑performance condition. Current AI servers rely on short‑reach copper interconnects that limit bandwidth and force dense processor layouts with intensive cooling. By moving optical links closer to the processor package, CScale aims to enable higher‑speed, longer‑distance data transmission while simplifying maintenance and reducing downtime. CEO Martin Lund, a former Cisco hardware executive, targets first chip shipments in 2028 for enterprise and cloud AI workloads.

💡 Reliable near‑chip optics could free data‑center architects from copper‑driven density and cooling limits, reshaping how performance and uptime are engineered.

techcrunch.com · Sep 30

Valor, Atreides, and Sequoia back AI startup Flow Engineering at $750M valuation

Flow Engineering, a San Francisco AI startup that automates hardware design, announced a $50 million Series B financing that values the company at $750 million. The round was co‑led by Antonio Gracias of Valar Equity Partners and Gavin Baker of Atreides Management, both known for backing Elon Musk ventures, and included participation from Sequoia Capital and former Sequoia partner Roelof Botha, who also joined Flow’s board. Flow’s platform deploys AI agents to align CAD drawings with product specifications, simulation outputs and testing data, aiming to streamline the traditionally labor‑intensive hardware development cycle. Existing customers span defense‑tech firm Anduril, electric‑vehicle maker Rivian, aerial‑mobility startup Joby Aviation, GM’s PPU joint venture, a Rivian‑Volkswagen JV, and space‑flight company Stoke Space. The funding will accelerate rollout and expand the design suite.

💡 Embedding AI into hardware design could dramatically shorten development cycles for advanced vehicles and aerospace systems, giving investors early influence over the next wave of AI‑driven manufacturing.

siliconangle.com · Sep 30

Low-energy chip startup Efficient Computer closes on $97M in funding

Efficient Computer, a startup developing data‑flow chips, announced a $97 million financing round led by TQ Ventures, with participation from Union Square Ventures, Toyota Ventures and Borderless. The new capital brings the company’s total funding to $650 million, following a $60 million round in February. Efficient’s architecture replaces traditional x86 CPU designs with a data‑flow model that it claims can cut power use by up to 100‑fold, potentially allowing devices to run for months or years on a single charge. Co‑founder and CEO Brandon Lucia said current AI accelerators trade programmability for efficiency, whereas Efficient’s chips aim to deliver high performance per watt without sacrificing general‑purpose computing. The firm is preparing to bring its first products to market in the next quarter soon.

💡 By slashing power draw dramatically, Efficient’s chips could make AI workloads viable in edge devices and data centers where electricity costs are a limiting factor.

siliconangle.com · Sep 30

World model startup General Intuition closes $220M investment

General Intuition Inc. secured $220 million in funding, valuing the company at $6.2 billion. The capital was led by Valor Equity Partners, Atreides, Seven Seven Six, Point72, Khosla Ventures, and General Catalyst. The startup, spun out of Medal B.V., builds world‑model AI that generates synthetic video for training purposes. Its latest algorithm, MIRA, can produce continuous, high‑resolution footage with complex object interactions at 20 fps on a single GPU, using latent diffusion to reduce memory usage. MIRA is currently a research demo, with a commercial version being tested with select robotics clients.

💡 By enabling limitless, efficient synthetic video generation, General Intuition could dramatically lower the cost and time required to train AI for robotics, potentially accelerating deployment across manufacturing and automation sectors.

quantumcomputingreport.com · Sep 30

NSF Awards $600,000 to Stony Brook and University of Hawaiʻi to Advance…

The National Science Foundation has granted $600,000 over three years to a joint effort by Stony Brook University and the University of Hawaiʻi at Mānoa to build Quantum Intelligent Sensor Networks (QISNs). Co‑led by Assistant Professors Hyeongrak “Chuck” Choi and Bo‑Han Wu, the project will shift quantum metrology from single‑sensor optimization to distributed, entangled sensor nodes. Researchers will combine continuous‑variable squeezed light, integrated photonics, and CMOS‑integrated diamond spin color centers, using quantum Fisher information to map sensitivity limits and assess how topology, loss, phase noise and entanglement affect performance. Wu’s team will model photonic circuits and apply quantum error‑correction techniques to mitigate environmental noise. The work aims to create design principles for long‑term deployments in ocean monitoring, disaster response, magnetic imaging and resilient communications.

💡 Demonstrating scalable, networked quantum sensing could unlock measurement precision unattainable by isolated devices, opening new frontiers for real‑world monitoring and secure communication.