PRODUCTS

How Cloudflare is raising the cost of AI hacking

As AI enables more cyber attack vectors, Cloudflare is making it harder to be an attacker.

On Monday, the cloud company launched Adaptive Intelligence, a continuous detection engine that autonomously learns from live traffic and generates rules on the fly that make automated attacks more expensive and time-consuming. The offering gives organizations a way to adaptively and instantly react to threat actors trying to breach their defenses. 

"Building taller walls fails when the cost of scaling an attack is effectively zero," Dane Knecht, CTO at Cloudflare, said in the company's announcement. "To stop modern bot threats, you have to flip the economics on the attackers. Traditional defenses offer a static target that threat actors can systematically solve."

By analyzing more than a trillion web visits every day to spot threats, Cloudflare said that Adaptive Intelligence acts like a "single, constantly learning brain." This allows you to:

• Implement "always-on" defense that retrains continuously on new types of breach techniques, instead of waiting for updates and scheduled releases

• Catch "low-and-slow" threats, such as credential stuffing and scraping, that typically go under the radar of traditional defenses

• Sift out real humans from malicious intent using behavior signals from Cloudflare Precursor, its continuous behavioral verification system

• Autonomously test and deploy upgrades to defenses behind the scenes with zero downtime

AI has given threat actors two significant advantages: the ability to undertake cyberattacks at a rapid pace and the ability to do so at very low costs. Cloudflare's system aims to nullify both of those advantages, creating a "moving target," said Knecht. 

This will only be more needed as frontier models emerge with cyber capabilities that are growing faster than even their creators have expected. It's a phenomenon that OpenAI has called attention to in recent weeks, pausing development of its unreleased frontier model, Astra, and calling for a global movement to strengthen cyber defenses broadly in a letter signed by a coalition of tech firms that included Cloudflare.

If there's anything that frontier model capabilities have revealed in recent months, it's that enterprises can't rely on a "set it and forget it" cybersecurity strategy. Additionally, security by obscurity, or having the hubris to think you won't be a target because you're too small or insignificant, is also no longer an option. Cloudflare's tool offers a creative option by hitting cyber attackers in the wallet. The tool's adaptability can help create a constantly evolving barrier that helps enterprises better brace themselves against creative attacks from AI models. The silver lining to frontier models' growing cyber attack capabilities is that this new cyber landscape is acting as a forcing function and the result could be new innovations in cybersecurity that will make enterprises more resilient. 

TOGETHER WITH GENERAL ASSEMBLY

The Talent Market Just Shifted. Are You Taking Advantage?

Something quietly changed in the talent market this year. As large companies cut jobs and rolled back benefits, experienced talent started moving—and a lot of it landed at SMBs. Nearly half of SMB HR leaders say they've already hired from larger firms in the past year, and most say recruiting has become noticeably easier because of it.

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STARTUPS

Can AI help crack interstellar travel?

AI is best known for transforming coding. Now, one startup is making the case for physics.

On Tuesday, the AI-native physics research lab, Physical Superintelligence (PSI), emerged from stealth with $58 million in seed funding, led by Breakthrough Energy. It is launching with two proofs of concept: 

1. A productized piece of its core platform, Emmy

2. Joining as a founding technical partner for the Fermi Explorer Mission, a nonprofit organizing the first privately funded interstellar space mission and the first AI-planned probe to Alpha Centauri

Emmy, named for renowned physicist Amalie Emmy Noether, combines PSI's reasoning engine, consisting of sovereign pre-trained and post-trained models, with a large curated inventory of simulations to tackle research problems at a pace much quicker than humans could, according to the company. Moreover, Emmy can reason through a problem, then test its conclusions until its findings are verifiable, as Matt Pines, co-founder and CEO, told The Deep View. 

"Our systems run research campaigns: they decompose a problem, generate candidate approaches, and test them against simulation, live measurement, or machine-checked proof," said Pines. "Nothing counts as a result until it survives a check that sits outside the model." 

Initially, a subset of Emmy's capabilities will be used for optimizing terrestrial and orbital AI data centers and factories. PSI has already signed commercial agreements and live pilot deployments on operating data center infrastructure today, according to Pines. 

The second prong of the launch is PSI's involvement in the Fermi Explorer mission, whose ultimate goal is to launch the first spacecraft to another star system, targeting Alpha Centauri, the closest star system to Earth. This initiative is a major undertaking because Alpha Centauri is roughly 4.37 light-years away, which would take about 80,000 years to reach from Earth at the speeds of current spacecraft. That makes it quite a feat of engineering to build a vessel capable of the journey. 

PSI has already claimed to have contributed to the mission by validating its physics and identifying a substantially more efficient trajectory within the mission’s mass and budget constraints. The company is using this finding to demonstrate that a small team using AI-native physics could do the work typically required of a national laboratory. This reflects the company's broader mission to contribute to discoveries that are both commercially and scientifically valuable.

"Fermi asked us to assess mission feasibility: the propulsion, trajectory, and power questions that determine whether the mission closes," said Pines. "Our technology ran the analysis, with our physicists directing the work. Fermi's technical team, which comes out of Starcloud, verified the analysis. The report was also written so the analysis can be rerun, and reproduction is the standard we want to be held to." 

PSI was founded by Pines, Alex Klokus, and Dr. Alexander D. Wissner-Gross, Ph.D, who 

combined to bring expertise across physics, economics, government, and tech. The broader team comprises physicists, AI researchers, experimenters, and builders, and PSI is actively hiring more talent. Interested applicants can apply online.

ChatGPT became the catalyst for the current AI boom, and since then, we have seen many companies try to compete by creating AI products. The result is that many of these products end up being repetitive or AI-washed offerings that have largely caused mainstream AI fatigue. However, some labs are developing focused, task-based AI solutions to solve big problems. Physical Superintelligence is a prime example, as it showcases just how instrumental AI can be as a catalyst to spur further innovation and development, even unlocking discoveries that have been very difficult to solve, with this extreme example of building a vessel capable of reaching Alpha Centauri. It's refreshing to see teams with ambitions this big. 

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The reproducible framework Lambda built boosts MFU by over 25% without changing the model itself. The entire framework is in this whitepaper, which also shows you how to address the memory inefficiencies inflating your costs, the training configurations that aren't making full use of your hardware, and the bottlenecks slowing down your GPUs

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HARDWARE

AI hardware has a smartphone problem

Manufacturers have unlocked a simple formula to capitalize on the AI hardware craze: take ordinary items, incorporate microphones, and layer in an AI assistant.

The promise is an AI tool that escapes the traditional screen and accompanies you everywhere. While these products often do that, the issue is that their main features are often duplicative, overlooking the fact that AI assistants are in a device that's always with you. On your phone, you already have a voice recorder that, when combined with an arsenal of apps that can transcribe, analyze, and answer questions, can already deliver what most of these AI devices do. 

A perfect example is a product I recently tried called the Flowtica Scribe, which calls itself "the world's first AI pen." If you are like my roommate and excitedly assumed an AI pen would do something groundbreaking, like digitally transcribe the words you write with it on paper, you may have the same reaction he did when finding out what it actually does. 

"That's it?" he asked.

The Scribe pen was designed to record audio within a 16-foot range with just a two-second press on the top of the pen. It transcribes the audio, provides summaries, answers questions about the conversations, and showcases the highlights or action items.

It's a perfectly capable product. When I used it to document the process of booking flights with my boyfriend, the transcript was accurate, even though the cafe was loud and I kept shifting the pen away from us to see if it could still hear our conversation. The summary graphic was so detailed that it remembered bits I hadn't even remembered, such as where our layover was, and presented it all in a digestible format. The more in-depth summary was accurate as well. 

But it'll cost you. The Flowtica Scribe retails for $159, or $209 for the Scribe and charging case, which offers up to one full week of battery life. There is also a basic AI plan that includes 300 AI minutes per month for all advanced features, with tiered plans for additional AI access at $10 or $20 per month. 

This highlights one of the biggest pitfalls of this category: the product comes at a surprisingly high cost for what it is because the hardware itself includes complex components, such as tiny processors and microphones. Plus, users typically have to shell out extra money for a subscription. 

Last week, Plaud unveiled its Plaud One AI-powered wireless earbuds, which record and transcribe audio, including phone calls, online meetings, and in-person conversations. The Plaud Agent is meant to "help turn conversations into useful output." 

The Plaud charging case includes an eSIM that has a wireless connection to bypass a phone. Again, I can't think of a situation where I would have earbuds and not my phone or laptop. And it costs $249, a price tag that rivals high-end ear buds like the AirPods Pro.

My concern is that this entire category of AI devices is watering down and muddying the definition of an AI product. Ultimately, AI is behind the scenes powering features small and large on most tech products. For instance, washing machines have used load-sensing and fabric-detection algorithms since the 2000s. By today's standards, would this make those AI products? I've been a fan of the AI hardware category since smart glasses were the only entrant. Smart glasses give AI context about the world around you, so you're not stuck feeding it that context yourself. Audio products technically do this, but audio is already easy to feed AI without extra hardware. Visual context is a harder problem. Short of holding up your phone in your line of sight at all times, there's no easy way to capture it. Solving this removes a genuine point of friction and lets you tap into AI in a far deeper way. That's the kind of thing we need out of AI devices: something you can't easily do with your phone.

LINKS

• Bankers paint a dystopian picture of how AI could manipulate markets

• Nvidia to invest $3.5 billion in MediaTek through convertible bonds 

• ChatGPT faces stricter EU scrutiny after surpassing 45 million user threshold

• OpenAI ad business hits $1 billion annualized revenue run rate

• Anthropic says bad actor used malware to hijack Claude login sessions

• Instagram to demote unlabeled AI-generated influencer accounts

• Cursor, OpenAI partnership to end November 12 after SpaceX acquisition

• Jumpcloud: AI agents need the same identity controls as your human workforce. See how to secure every identity, human or not. (sponsored)

• OpenClaw 2.0: the AI agent got its biggest update ever, with improvements to setup, a new browser app, and updates to memory, messaging, skills, and automations

• OpenAI Codex: hit 25M active users; reset usage for all paid subscriptions

• Apodex 1.1: Apodex's first model on Artificial Analysis; scores 44, performing on par Kimi K2.6 (45), MiniMax-M3 (45), and Inkling (42)

• ChatGPT: can now connect multiple Gmail and Google Calendar accounts

• Duckie: AI Agent Engineer

• OpenAI: Data Scientist, Cybersecurity

• Google DeepMind: Research Engineer, Conversational Agentic AI, DeepMind

• NVIDIA: Applied AI Engineer

GAMES

A QUICK POLL BEFORE YOU GO