A Zhuhai operator used DeepSeek, a Hermes agent and a bundled godmode jailbreak to hunt more than 460 targets, then stole data from three organisations. Open-weight models this week made that offensive kit a public shopping list for any lone operator who can still point one at his scanner tonight.
Taiwan confirmed AI agents ran a July government intrusion through weak credentials, not a zero-day. For Australian CISOs, last year's backlog has been repriced. Close hygiene, treat agents as privileged identities, and rehearse at machine speed before the next quarterly drill. The estate is open.
AMD's proposed Taalas acquisition targets the fast-growing AI inference market, adding specialised silicon technology designed around model-specific workloads to its Instinct, EPYC, Helios and ROCm platform.
Mercor, a $2B AI hiring platform, leads the AI startup boom, processing 300K candidates with precision. As vertical AI reshapes industries, its rise echoes the internet’s early days, fueling efficiency and innovation. AI’s next trillion-dollar shift is here.
The AI startup landscape is in full swing, shifting from AI revolution to AI evolution. Applied AI is taking center stage, moving beyond foundational models into specialized AI agents and vertical solutions reshaping industries. Leading this charge is Mercor, an AI-driven hiring platform now valued at $2 billion, which is redefining recruitment with its hybrid AI model.
Founded by three 21-year-olds, the platform has processed 300,000 candidates and 100,000 AI-powered interviews since 2023, automating hiring decisions with a speed and precision that has driven an eightfold valuation increase in just five months. Last week, CEO Brendan Foody, speaking on CNBC’s Squawk Box, stated that Mercor’s AI models are trained to predict job performance with greater accuracy than traditional hiring methods.
But as Mercor streamlines hiring through algorithmic decision-making, it raises fundamental questions: Does this technology create a fairer hiring process, or does it commodify human potential into mere data points?
Mercor is solving talent allocation in the AI economy.
— Mercor (@mercor_ai) February 20, 2025
The difference between greatness and failure is the right person being in the right place at the right time. Putting them there is the hardest unsolved problem in capitalism.
We’re excited to announce our $100M Series B at… pic.twitter.com/GbMIAh1Wee
Mercor isn’t alone in this AI gold rush. The incredible pace of AI innovation is mirroring the late-1990s to early-2000s unicorn race that fueled the proliferation of the internet. Several AI startups are fast approaching the $1 billion+ unicorn club, driven by breakthroughs in vertical AI applications. Inceptio Technology ($678M in funding) is revolutionizing autonomous trucking, slashing logistics costs by 38% and reducing accident rates by 73% in pilot programs.
Celestial AI ($370M) is pushing the frontiers of photonic computing, accelerating neural network training 9x faster with optical interconnects. Meanwhile, SiMa.ai ($850M valuation) is transforming edge AI with real-time 4K video analytics, and Genesis Therapeutics ($900M) is using deep learning to cut drug discovery timelines from 18 months to just 23 days. AutoX ($950M) is redefining urban mobility with the largest robotaxi fleet in China, completing 43 million paid rides in 2024.
While these AI unicorns are driving unprecedented innovation, Mercor’s model highlights the tension between efficiency and ethics. As shown by Mercor CEO Brendan’s tweet, the company is growing at an incredible pace, hiring 800 people in a single week.
we hired 800 people this week
— Brendan (can/do) (@BrendanFoody) February 22, 2025
Its financials are staggering—51% monthly revenue growth, 89% gross margins, and $1.79 million annualized revenue per employee—yet independent audits flag systemic biases. Women score lower on communication, older applicants face higher rejection rates, and Ivy League graduates dominate opportunities. Mercor claims its algorithms correct for bias, but its black-box nature leaves regulators uneasy. With GDPR and EEOC compliance concerns mounting, Mercor’s fate will test the limits of AI-driven hiring.
Mercor’s ambitions extend beyond hiring, eyeing education admissions and tokenized earnings, aiming to redefine human capital management entirely. But as AI-powered decision-making expands, the central debate remains:
Will AI empower people or trap them in algorithmic efficiency machines?
If trends continue, AI will mediate 90% of hiring decisions by 2028, a transformation that could either optimize global labor markets or deepen inequalities.
As we continue tracking the incredible young minds driving and AI startups in this AI revolution—alongside success stories like Notion—2025 is shaping up to be a breakout year for AI startup adoption. Venture capital and private equity are rapidly converging to build a supercluster of AI companies beyond the usual titans like OpenAI, Anthropic, and Perplexity. The trend is only getting stronger, with vertical AI emerging as the next great utility—specialized models designed to seamlessly integrate into industries from finance and healthcare to logistics and cyber security. These AI solutions aren’t just optimizing workflows; they’re fundamentally rewiring how businesses operate and how consumers interact with technology, shifting the balance of power in the digital economy.
From a CNC editorial vantage point, it’s abundantly clear this AI evolution is charging ahead with remarkable speed—far beyond mere hype. SpaceX CEO Elon Musk sparked fresh debate on June 20, 2024, when he proclaimed AI the linchpin to an “age of abundance” that could usher in Universal High Income, even as he sounded the alarm over a “crisis of meaning” and a disconcerting “10-20% chance of annihilation.” But Musk isn’t the only visionary heralding AI’s game-changing potential. Anish Acharya, a general partner at Andreessen Horowitz (a16z), has spotlighted AI as a driving force of economic realignment—liberating creativity, self-expression, and more profound avenues of work. In 2024, Acharya likened AI’s disruptive power to the plow and microchip, two innovations that exponentially increased productivity and enriched entire societies.
NVIDIA is asking Wall Street to underwrite AI compute as productive infrastructure. Its new financing platforms aim to mobilise more than US$500 billion, but the announced memoranda are not yet completed funding commitments.
Washington is pushing its AI security perimeter deep inside the data centre, targeting Chinese-made components that move data between GPUs. The policy may reduce cyber and espionage risks, but it could also raise costs, slow construction and expose a new weakness in America’s AI race as AI scales.
Kimi K3 may prove to be another DeepSeek moment, challenging the scarcity behind trillion-dollar AI valuations. As open intelligence spreads, frontier models may become utilities, while the greater prize shifts to the nations, industries and people bold enough to build with them and share freely.
We are racing to shape our AI future through a new Office of AI and national standards. Yet billions flow into foreign-led data centres while we offer little support for local models or sovereign compute. Without stronger action we risk becoming high-quality hosts rather than true leaders.
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