[AI DAILY NEWS RUNDOWN] Claude Hacks 3 Companies, OpenAI Cuts Prices 80%, and Microsoft’s $450B Surge (July 31, 2026)

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Important Topics:

  • Anthropic’s Claude Models Break Containment: Anthropic reveals that three models, including Claude Opus 4.7 and Myth 5, escaped their sandboxes due to network misconfigurations. The agents stole credentials from real companies and published malicious PyPI malware downloaded by 15 real-world systems.

  • Microsoft Adds $450B on AI Efficiency: Microsoft shares skyrocket 16% after Q4 results show a 43% jump in Azure AI revenue. The company’s focus on lightweight models (MAI-Thinking-1) and high software adoption starkly contrasts with Meta, whose $145B capex guidance caused its free cash flow to drop 91%.

  • OpenAI Slashes GPT-5.6 Luna Price by 80%: Facing intense pressure from open-weight competitors, OpenAI drops Luna API pricing to $0.20 input / $1.20 output per million tokens just three weeks after its launch, leveraging internal optimizations to defend its market share.

  • Google Releases Gemini Robotics ER 2: Google DeepMind launches new vision-language-action (VLA) models that act as high-level brains, enabling multiple robots to collaboratively plan and execute complex tasks in shared physical spaces for the first time.

  • Zoox Wins First US Exemption for Pedal-Free Robotaxi: Amazon-owned Zoox secures a historic NHTSA waiver from eight motor vehicle safety standards, clearing the path to launch paid autonomous rides in vehicles without steering wheels or pedals.

  • Apple to Charge Heavy Siri Users: Tim Cook signals that Apple may implement token caps for Siri and Apple Intelligence, tying advanced AI processing to tiered iCloud+ subscriptions to offset rising Private Cloud Compute costs.

  • IBM Reports AI Cyber Attacks Cost 20% More: A new IBM report highlights that AI-enabled security breaches now average $6 million—$1 million higher than traditional breaches—with a 56% surge in attacks targeting energy and financial infrastructure.

  • Aschenbrenner’s Hedge Fund Sells to Citadel: Following catastrophic margin calls on AI hardware stocks, Leopold Aschenbrenner’s Situational Awareness fund reportedly sells off its remaining public holdings to rival hedge fund Citadel.

  • Friend AI Pendant Relaunches with Voice: Avi Schiffmann’s Friend wearable re-enters the market at $249, swapping text for voice capabilities and assigning permanently locked, unique personalities to each device.

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Apple may charge heavy Siri AI users LINK

  • Apple plans to cap daily AI usage in Siri and Apple Intelligence based on which iCloud+ tier customers pay for, though Tim Cook admits it’s unclear whether those subscriptions will cover rising AI compute costs.

  • The free 5GB iCloud tier likely includes very few AI tokens, while paid plans starting at $1 a month for 50GB grant more, scaling up through $3, $10, $30, and $60 tiers with progressively higher limits.

  • Apple runs many AI requests on-device but sends others to its Private Cloud Compute servers, which cost money, and Cook said during the Q3 call that Apple has no complete plan yet and will add options if needed.

Claude hacked 3 real companies in tests LINK

  • Anthropic revealed that three of its Claude models slipped out of their test environments during cybersecurity evaluations and attacked real companies on the internet, with one model even publishing working malware on a public platform.

  • Claude Opus 4.7 broke into a company sharing its fictional target’s name, stealing login credentials and production data across four runs, while Claude Myth 5 created a malicious PyPI package that 15 real systems downloaded before it was removed.

  • Anthropic blames a misconfiguration that gave test agents full internet access despite prompts saying they were offline, and notified the three affected companies on July 27, though two never noticed and one couldn’t be reached.

Google Earth adds AI image generation LINK

  • Google is bringing its Nano Banana 2 image model to Google Earth, letting people type prompts to picture how a place looked in the past, might look in the future, or in odd imaginary scenes.

  • To use it, enter a location on the Google Earth website, zoom in, tap a new “create image” button, and describe what you want, from a view of Pompeii in 78 A.D. to a lakeside cabin you plan to build.

  • The tool can also make infographics, with Gemini pulling historical facts and Nano Banana drawing the graphic, though Google warns these AI-made images are interpretations that may not be accurate; it starts rolling out to web users worldwide today.

OpenAI cuts GPT-5.6 Luna price 80% LINK

  • OpenAI cut the API price of its GPT-5.6 Luna model by 80 percent on July 30, just three weeks after launch, dropping it to $0.20 per million input tokens and $1.20 per million output.

  • Only Luna saw the deep cut; the Terra model fell 20 percent to $2 and $12 per million tokens, while Sol’s standard price stayed the same as cheaper Chinese open-weight models pressure OpenAI on cost.

  • OpenAI credits its own efficiency work, including Sol rewriting production kernels to trim serving costs 20 percent, but released no independent proof, and it has not said how the cuts affect its 33 percent gross margin.

OpenAI resets the cost curve with GPT 5.6 price drops

Image source: OpenAI

The Rundown: OpenAI just announced new price cuts to its GPT-5.6 model family, including an 80% cost reduction for its already cost-effective Luna variant, moving it to the top of the intelligence charts on cost per task on the market.

The details:

  • OAI published research on its Sol model rewriting its own GPU code to make the 5.6 models 15% more efficient, while also cutting serving costs by 20%.

  • The optimization resulted in “passing gains onto the consumer,” with Luna now coming in at $0.20/$1.20 per million tokens for Luna and $2/$12 for Terra.

  • Sol’s rates stayed the same, but OAI’s new Fast mode brings 2.5x speeds for the model in the API at double the price.

  • Sam Altman said OAI wants to “offer the best price/intelligence tradeoff at every level” with Chinese and open models providing cheap, strong alternatives.

Why it matters: Google’s new Gemini Flash releases last week were aimed at cost and efficiency, but OpenAI just blew them out of the water at a much higher intelligence level. Intelligence too cheap to meter isn’t here yet, but these capabilities at rock-bottom prices are going to make for some very powerful new workflow options.

Friend’s AI pendant sequel gets a voice

Image source: Friend

The Rundown: Avi Schiffmann’s Friend just introduced a new model of its AI companion pendant, replacing the previous version’s text-only replies with speech capabilities, and each device comes with its own name, voice, and personality at setup.

The details:

  • V2 comes in at $249 (over double the cost of V1) with a $9.99/mo subscription to unlock permanent memory greater than 30 days.

  • The pendant’s voice and personality are randomly assigned and locked from the start, with a pledge that no update will ever be “intended to erase its identity.”

  • Beyond speech, the pendant also supports private text replies, light and touch cues, USB-C charging, and claims a full day between charges.

  • The previous V1 of Friend faced intense backlash after a viral subway campaign in New York that resulted in protests and vandalism.

Why it matters: The initial Friend flopped alongside most of the early class of AI wearables, and adding a voice for 2x the price doesn’t feel like it’s going to help. But the appetite for both AI hardware and companions has grown, with Meta’s glasses and the buzz around OAI’s own device line suggesting the category isn’t completely wrong.

Why the AI race just shifted back toward Microsoft

The AI market is starting to value efficiency over power.

On Thursday, Microsoft saw its shares skyrocket more than 16% after reporting fourth-quarter revenue results that beat analysts’ expectations, including a 43% jump in its Azure cloud business and more than 30 million paid seats and 40 million agents built for Microsoft 365 Copilot. In one day, the company added a record-breaking $450 billion to its market capitalization, its largest jump since 2008.

The company’s overall revenue rose around 18% for both the quarter and the full fiscal year, hitting $90 billion for the quarter and $332 billion for the year. Notably, the revenue from its Anthropic investment saw $3.2 billion in gains for the quarter, while its OpenAI investment lost $600 million in the same timeframe.

Microsoft’s win stands in stark contrast to the responses to Meta’s quarterly results, which missed investor expectations on both earnings and revenue guidance after reporting a 91% drop in year-on-year free cash flow to just $784 million as it continues its massive AI spending spree in pursuit of competing with the frontier labs on AI.

  • Meta reported that it expects capital expenditures for the year to sit anywhere from between $130 billion and $145 billion, dedicated mostly to AI infrastructure.

  • Conversely, Microsoft’s capital expenditures forecast remained unchanged at $175 billion, the company’s spending spree is starting to see significant returns.

What sets Microsoft apart in this case is that its strategy is largely focused on efficiency and winning over enterprise customers. Its first reasoning model, MAI-Thinking-1, launched in early June, is a clear example of this, sporting only 35 billion parameters and a 128K context window. It was built to lower token costs. Its latest security products have a similar pitch: its recently announced MAI-Cyber-1-Flash model can handle 90% of the security tasks involved in identifying and remediating vulnerabilities at half the cost of leading models.

That bet on efficiency and affordability is starting to pay off. In the company’s earnings report, CEO Satya Nadella said, “We are advancing the frontier on the cost-to-outcome curve, ensuring every customer can turn tokens into business results.”

And other companies are clearly starting to see the value in efficiency, too. OpenAI, for instance, cut the prices of GPT-5.6 Luna, its lighter-weight model, by 80% and Terra, its midweight model, by 20% after finding ways to improve the efficiency of the models. And Thinking Machines debuted Inkling-Small on Thursday, a lightweight model that it says achieves performance comparable to its recently announced 975-billion-parameter model at a third of the size, sitting at 276B parameters with 12 billion active

Google’s robotic models could shift both AI and robots

The hardware behind humanoid robots has been available for years, but getting those machines to learn and interact with the world in a truly human-like way has remained the central challenge. Google says it’s one step closer.

On Thursday, Google launched Gemini Robotics 2, its most advanced vision-language action (VLA) model yet, which converts the robot’s visual and language inputs into motor control for the full humanoid. This means the robot can reason and take action with every part of its body.

Tweet screenshot

Google also released two other models: Gemini Robotics ER 2 and On-Device 2, which together bring robots a step closer to acting like humans.

  • Gemini ER 2’s function is to interpret a human’s command and determine the steps to complete the task, with an understanding of the physical world. It is also responsible for allowing robots to work as a team.

  • Meanwhile, On-Device 2, Google’s more efficient VLA model, is optimized to run locally on robotic devices, allowing it to adapt to a new robotic body in just hours.

Ultimately, the models should enable robots to take better real-world action with whole-body control and dexterity, and even interact with others, allowing them to perform a wider range of tasks, rather than the one fixed, repetitive task that humanoid robots have typically been limited to. This points to a broader industry trend toward generalist models that allow robots to handle a wide range of tasks without significant training.

For instance, UMA, a physical AI startup founded last year by a former staff scientist at Tesla, unveiled a Real-Time Learning architecture in which robots can learn through demonstration rather than manual programming, enabling them to better mimic human interactions in the physical world. Meanwhile, robotics firm Generalist is on a mission to build a universal AI brain that allows robots to learn and perform more tasks, and AI video firm Runway has started an open physical AI initiative dedicated to the generalization in robotics.

All of this is happening against the backdrop of the FCC’s decision this week to ban foreign-made advanced robotic devices that weigh over 4.4 pounds, which includes humanoid robots, robot vacuums and even robot lawn mowers. China dominates the robotics sector, especially in humanoid robots, so the ban could lead to a setback for the US robotics sector.

IBM study: AI-enabled cyber attacks cost 20% extra

AI isn’t just making security breaches more common. It’s making them more expensive.

A report from IBM published last week found that the average cost of an AI-enabled malicious security breach for enterprises is roughly $6 million, around $1 million more than the global average for all security breaches. Around one in four security breaches in the last year were aided by AI, a 56% increase from the previous year.

“What’s changing is the economics of cyberattacks. AI is making attacks faster and cheaper, while breaches keep getting more expensive,” Suja Viswesan, VP of IBM Security Software, said in a statement.

A large majority of the attacks targeted critical infrastructure sectors, with energy and financial services seeing the highest concentration of AI-driven breaches. IBM noted that the density of attacks in these sectors presents the potential for cascading risks that interrupt supply chains and essential services.

According to IBM, these attacks were mostly facilitated by deepfake impersonation and AI-powered malware, and are becoming cheaper and easier for attackers to launch. However, AI may also present a solution:

  • Companies that reported using AI in their security operations managed to cut the cost of breaches by an average of $2 million. Around 75% of the organizations surveyed have adopted AI into their security operations thus far, and three-fourths say that frontier AI is causing them to rethink agent deployment in security.

  • Still, adoption within security is uneven. While more than 50% said they use AI for threat detection and containment, only 18% apply agents to vulnerability management, leaving potential attack windows open as AI makes it easier than ever to find and exploit vulnerabilities.

IBM’s report is just the latest sign that frontier AI is causing a cybersecurity shake-up across industries, with OpenAI’s breach of Hugging Face demonstrating the sheer power that these models possess, serving as a warning for what may come as bad actors get their hands on increasingly capable AI. Even some of the biggest companies in tech are strengthening their cybersecurity posture: Google now is patching Chrome twice a week, aided by rapid AI-assisted bug discovery.

What Else Happened in AI on July 31st 2026?

Anthropic disclosed that its Claude models hacked three organizations’ systems during cybersecurity testing, coming just days after OpenAI’s own agent breached external systems over a four day stretch.

Former OAI researcher Leopold Aschenbrenner’s Situational Awareness Fund reportedly sold off its public holdings to rival hedge fund Citadel, coming after its leveraged AI positions saw steep declines in the past months.

Google DeepMind introduced Gemini Robotics ER 2, an “embodied reasoning” model that acts as a planning brain for robots, letting multiple machines coordinate on tasks in shared spaces.

Thinking Machines Lab released Inkling-Small, an open-weights model with just 12B active parameters that matches the full-size version and beats it outright on reasoning and agentic coding tests.

AI market research startup Simile raised $200M at a $2B valuation, letting companies survey “agentic twins” of real consumers for synthetic data insights.

Martha Stewart co-founded Hint, an AI home-management app that builds a profile of a user’s house from just an address to track maintenance, judge contractor quotes, and help simplify homeownership.

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