For years, the narrative around large language models was simple: the most capable models lived behind APIs, and open-source alternatives trailed behind by a generation or two. Open models were good for experimentation, research, or cost-sensitive use cases — but not for serious, production-grade intelligence.
That narrative has collapsed. — Read More
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NEW Seedance 2.0 is INSANE!
An ice dance duo skated to AI music at the Olympics
Czech ice dancers Kateřina Mrázková and Daniel Mrázek made their Olympic debut on Monday, an unfathomable feat that takes a lifetime of dedication and practice. But the sibling duo used AI music in their rhythm dance program, which doesn’t break any official rules, but serves as a depressing symbol of how absolutely cooked we are.
As Mrázek spun his sister in a crazy cartwheel-lift-sort-of-move that made them look superhuman, one of the NBC commentators mentioned in passing, “This is AI generated, this first part,” referring to the music. Somehow, that admission is even more baffling than the gravity-defying tricks that the siblings showed off on the pressure of Olympic ice. — Read More
America’s $1T AI Gamble
The United States is undertaking a historically unprecedented investment boom to build the computers, data centers, and other physical infrastructure needed to train and deploy Artificial Intelligence. Hundreds of billions of dollars have already been spent by hyperscalers racing to build smarter AI systems, and investment from major tech companies is set to shatter all previous records again this year. Amidst this boom, spending on data center construction has hit a new record high, now exceeding a $42B annualized pace, a more than 300% increase since the launch of ChatGPT in late 2022. While growth has slowed over the last six months, investment is still up more than 18% over the last year alone.
Yet that figure only reflects the costs to build data center facilities themselves, not the much larger costs of the expensive GPUs, TPUs, and other electronics housed within. Real US fixed investment in those computers and related peripheral equipment has surged to a record high of more than $270B annualized, up nearly 50% over the last year and up 77% since ChatGPT’s launch.
… America is making a globally and historically unprecedented bet on the success of Artificial Intelligence. As a share of the economy, that AI boom is already one of the largest investments in American history—dwarfing the peak of the broadband, electricity, or interstate highway buildouts and vastly exceeding the Manhattan or Apollo projects. And yet, US tech companies are doubling down, raising the stakes on their $1T gamble that AI models will continue their exponential capabilities growth and eventually become valuable enough to repay such a colossal investment. — Read More
The SaaSpocalypse – The week AI killed software
The week AI killed software
Last Monday, $285 billion of market cap evaporated from software, financial services, and asset management stocks. Thomson Reuters lost $8.2 billion. In a single day. LegalZoom dropped 20%. India’s Nifty IT index posted its worst month since October 2008 — worse than the financial crisis.
he week AI killed softwarexxxxLast Monday, $285 billion of market cap evaporated from software, financial services, and asset management stocks. Thomson Reuters lost $8.2 billion. In a single day. LegalZoom dropped 20%. India’s Nifty IT index posted its worst month since October 2008 — worse than the financial crisis. — Read More
AI-Generated Text and the Detection Arms Race
In 2023, the science fiction literary magazine Clarkesworld
stopped accepting new submissions because so many were generated by artificial intelligence. Near as the editors could tell, many submitters pasted the magazine’s detailed story guidelines into an AI and sent in the results. And they weren’t alone. Other fiction magazines have also reported a high number of AI-generated submissions.
This is only one example of a ubiquitous trend. A legacy system relied on the difficulty of writing and cognition to limit volume. Generative AI overwhelms the system because the humans on the receiving end can’t keep up. — Read More
Reinforcement World Model Learning for LLM-based Agents
Large language models (LLMs) have achieved strong performance in language-centric tasks. However, in agentic settings, LLMs often struggle to anticipate action consequences and adapt to environment dynamics, highlighting the need for world-modeling capabilities in LLM-based agents. We propose Reinforcement World Model Learning (RWML), a self-supervised method that learns action-conditioned world models for LLM-based agents on textual states using sim-to-real gap rewards. Our method aligns simulated next states produced by the model with realized next states observed from the environment, encouraging consistency between internal world simulations and actual environment dynamics in a pre-trained embedding space. Unlike next-state token prediction, which prioritizes token-level fidelity (i.e., reproducing exact wording) over semantic equivalence and can lead to model collapse, our method provides a more robust training signal and is empirically less susceptible to reward hacking than LLM-as-a-judge. We evaluate our method on ALFWorld and Bench and observe significant gains over the base model, despite being entirely self-supervised. When combined with task-success rewards, our method outperforms direct task-success reward RL by 6.9 and 5.7 points on ALFWorld and Bench respectively, while matching the performance of expert-data training. — Read More
Python or C++ for AI? Here’s the Honest Answer After Years of Using Both
Forget the hype. This is what really happens when you build AI systems in Python and C++, and why the “one language” debate misses the point.
On the surface, it sounds like a simple “this or that” question. But if you’ve actually built stuff — broken stuff, fixed stuff at midnight, and argued with teammates over which language is better — you know it’s not that simple. The short version? You probably need both. The long version? Well, that’s what this post is about. — Read More
Authentication Downgrade Attacks: Deep Dive into MFA Bypass
Phishing-resistant multi-factor authentication (MFA), particularly FIDO2/WebAuthn, has become the industry standard for protecting high-value credentials. Technologies such as YubiKeys and Windows Hello for Business rely on strong cryptographic binding to specific domains, neutralizing traditional credential harvesting and AitM (Adversary-in-the-Middle) attacks.
However, the effectiveness of these controls depends heavily on implementation and configuration. Research conducted by Carlos Gomez at IOActive has identified a critical attack vector that bypasses these protections not by breaking the cryptography, but by manipulating the authentication flow itself. This research introduces two key contributions: first, the weaponization of Cloudflare Workers as a serverless transparent proxy platform that operates on trusted Content Delivery Network (CDN) infrastructure with zero forensic footprint; second, an Authentication Downgrade Attack technique that forces victims to fall back to phishable authentication methods (such as push notifications or OTPs) even when FIDO2 hardware keys are registered. — Read More
My AI Adoption Journey
Mitchell Hashimoto, a HashiCorp co-founder, shares his approach to AI adoption.
My experience adopting any meaningful tool is that I’ve necessarily gone through three phases: (1) a period of inefficiency (2) a period of adequacy, then finally (3) a period of workflow and life-altering discovery.
In most cases, I have to force myself through phase 1 and 2 because I usually have a workflow I’m already happy and comfortable with. Adopting a tool feels like work, and I do not want to put in the effort, but I usually do in an effort to be a well-rounded person of my craft.
This is my journey of how I found value in AI tooling and what I’m trying next with it. In an ocean of overly dramatic, hyped takes, I hope this represents a more nuanced, measured approach to my views on AI and how they’ve changed over time. — Read More
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