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  • BMW and ByteDance deepen AI cooperation

BMW and ByteDance deepen AI cooperation

Also: Thailand unveils “AI Police Cyborg 1.0”

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AI KATANA
April 20, 2025

Hello!

In today’s edition, we explore how AI is reshaping industries, geopolitics, and creative expression. BMW is doubling down on AI in China through an expanded alliance with ByteDance’s Volcano Engine, aiming to revolutionize digital customer engagement. Meanwhile, India marks a milestone in tech sovereignty by launching its first home-grown AI server, potentially shifting the regional hardware landscape. Thailand’s new AI-powered police robot debuts just in time for Songkran, adding a layer of smart surveillance to public safety. On the cultural front, the rise of AI-generated “doll” imagery has triggered fierce backlash from artists who argue for the irreplaceable value of human-made creativity. In the U.S., Congress is applying pressure on federal agencies to implement stricter AI governance, underscoring rising scrutiny over public-sector AI deployments. Meanwhile, new benchmark data reveals OpenAI’s latest models are smarter—but also more prone to hallucination, raising tough trade-offs for enterprise users. And rounding out the update, OpenAI rolls out memory features for ChatGPT while VC money flows into AI security innovation.

Sliced just for you:

  • 🚘 BMW and ByteDance deepen AI cooperation

  • 🇮🇳 India Debuts Home‑Built AI Server

  • 🤖 Thailand unveils “AI Police Cyborg 1.0”: Smart robot officer joins force to enhance Songkran safety

  • 👧 AI dolls are taking over - but real artists are sick of them

  • 🏛️ Congress Demands AI Standards at DOGE

  • 🤔 Hallucination Spike in OpenAI’s New Models

BMW is intensifying its collaboration with ByteDance’s Volcano Engine to enhance marketing and service operations using AI, under its Holistic AI Strategy in China. The initiative, spearheaded by BMW Brilliance's digital arm Lingyue Digital Information Technology, focuses on applying AI-driven tools for personalized content delivery, real-time customer interactions, and immersive digital experiences. By harnessing Volcano Engine’s capabilities in large language models and recommendation algorithms, the partnership aims to streamline product recommendations, optimize customer service, and support the continuous evolution of AI models. This deepened alliance builds on a relationship established in 2019, signaling BMW’s long-term commitment to digital innovation and intelligent transformation within the Chinese market.

India unveiled its first domestically manufactured AI server in Gurugram, with IT minister Ashwini Vaishnaw hailing the rack‑scale machine as a strategic leap toward silicon sovereignty. Built around a locally assembled GPU array capable of 1.2 petaflops of mixed‑precision throughput, the server will anchor a planned national compute grid that feeds academic labs and startups via subsidized credits. Officials claim the indigenous design slices import costs by 35 percent and halves lead times compared with sourcing from abroad. The launch coincides with New Delhi’s draft guidelines mandating that sensitive governmental AI workloads run onshore, a policy expected to turbocharge domestic hardware demand. Pilot deployments are set to begin at IIT Delhi next month, with a commercial variant targeted for Q4 export to Southeast Asia. Industry observers view the project as India’s answer to China’s Ascend and the EU’s EPI programs.

Thailand has introduced its first AI-powered police robot, “AI Police Cyborg 1.0,” to bolster safety during the country’s Songkran festival. Deployed in Nakhon Pathom province, the Robocop-style unit is equipped with 360-degree AI cameras and integrates real-time surveillance data from CCTV and drones. The system is capable of facial recognition, suspect tracking, weapon detection, and behavior monitoring, offering alerts for high-risk individuals and disruptive conduct. Jointly developed by local police authorities and the municipality, this initiative marks a significant step in Thailand’s adoption of AI for public security, aiming to enhance crowd management and situational awareness at major events.

A growing backlash is emerging among artists and illustrators in response to the viral trend of AI-generated “starter pack” doll images, which critics say threatens creative livelihoods and dilutes artistic authenticity. Since early April, thousands have uploaded selfies to be transformed into toy-like images via AI tools, igniting concerns over intellectual property, environmental impact, and data privacy. Artists like Nick Lavellee, known for handcrafted action figures of cultural icons, express frustration as AI art floods social media, undermining both the value and perception of handmade work. The grassroots #StarterPackNoAI movement has rallied creatives worldwide to push back with their own human-made artworks, emphasizing the irreplaceable humanity, effort, and individuality behind traditional artistic methods. While some acknowledge AI’s potential as a creative aid, many argue its misuse in gimmicky applications trivializes its true capabilities, wasting innovation on digital novelties instead of solving meaningful problems.

A bipartisan group of U.S. lawmakers sent a sharply worded letter to the Administration’s new Department of Government Efficiency, warning that its rapid deployment of AI decision systems across procurement and HR lacks minimum standards for data security and oversight. The representatives cite instances where unvetted models accessed personnel files and sensitive vendor bids, potentially violating federal privacy statutes. They demand an immediate inventory of all models in production, publication of risk assessments, and the appointment of an independent chief AI officer. The letter foreshadows a broader push in Congress to graft NIST’s voluntary AI risk framework onto mandatory agency rules. Analysts note the timing: the House is finalizing its FY 2026 appropriations bill, and funding for the department could hinge on compliance. The agency has ten days to respond, setting up a potential public hearing in early May.

Fresh benchmark data suggest OpenAI’s latest reasoning‑focused models, o3 and the lighter o4‑mini, outperform their predecessors on multi‑step math and coding tasks yet exhibit a higher incidence of hallucination when asked to generate factual prose. In stress tests over 5,000 Wikipedia‑style queries, o3 hallucinated 11 percent of the time, up from 7 percent for GPT‑4‑Turbo, while o4‑mini clocked in at 13 percent. Engineers attribute the spike to aggressive mixture‑of‑experts routing that prioritizes reasoning depth over retrieval grounding. OpenAI argues that chain‑of‑thought transparency enables users to spot errors faster, but researchers counter that corporate users expect accuracy without manual vetting. The findings reignite the debate over whether bigger context windows and deeper reasoning inevitably trade off against truthfulness, and they arrive as enterprise buyers weigh model selection before renewing annual contracts in June.

🛠️ AI tools updates

OpenAI began rolling out memory for ChatGPT, letting the assistant store user preferences and project details that persist across sessions. Users can instruct the bot to remember writing style, recurring acronyms, or ongoing tasks; data is encrypted at rest and editable or deletable in a new Memory Manager dashboard. Early testers say workflows such as weekly status‑report drafting now require half the prompts. Enterprise admins gain tenant‑wide controls to disable memory or force automatic redaction of sensitive fields. OpenAI frames the feature as a step toward a personalized workspace agent, though privacy advocates caution about inadvertent retention. Paid tiers get larger memory slots, while free users receive a smaller quota. The rollout starts on the web today and reaches mobile apps next week, with opt‑in prompts appearing after three related conversations.

💵 Venture Capital updates

Pillar Security, a Boston‑based startup focused on monitoring AI models for jailbreaks and data‑leakage exploits, closed a $9 million seed round led by Accel with participation from HearstLab and several former NSA engineers. The company’s SaaS platform probes prompts in real time, flagging suspicious transformations and auto‑patching model weights through reinforcement learning. Early pilots at two Fortune 100 insurers claim a 30 percent drop in policy‑holder data exposure. The round values Pillar at roughly $48 million post‑money, according to sources close to the deal. The fresh capital will fund expansion of Pillar’s red‑team lab and accelerate hiring of threat analysts ahead of a planned SOC 2 audit this autumn. Management says the seed funding gives 18 months of runway and positions Pillar to pursue a Series A once its agent‑based remediation hits general release later this year.

🫡 Meme of the day

⭐️ Generative AI image of the day