Good morning. It’s Wednesday, July 2nd.
On today in tech history: In 1997Apple dropped the Newton Web Enabler 2.0, upgrading the Newton PDA’s TCP/IP stack for higher 9600-baud modem connectivity. This networked leap hinted on the cloud infrastructure AI apps would later devour
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Today’s trending AI news stories
Mark Zuckerberg broadcasts his AI ‘superintelligence’ super-group
Meta has launched Meta Superintelligence Labs (MSL), a full-stack overhaul of its AI operations aimed squarely at constructing human-level and beyond AI systems. This latest division absorbs FAIR, Llama, and product AI teams into one streamlined unit with a transparent mandate: move faster, scale larger, dominate the space.

Leading MSL is Alexandr Wang, now Chief AI Officer at Meta, fresh off a $14.3 billion deal to soak up Scale AI. He’s joined by Nat Friedman and Daniel Gross, names synonymous with deep AI and startup firepower.
Zuckerberg isn’t hiding the ambition: Meta is raising $29 billion for next-gen compute and data centers. While critics call the pursuit of “superintelligence” speculative, Meta is treating it as a matter of when, not if. With OpenAI and Google under pressure to retain top talent and keep pace, Meta’s daring consolidation marks a decisive escalation within the AI arms race. Read more.
Apple reportedly considers letting Anthropic and OpenAI power Siri
Apple is recalibrating its AI strategy, shifting from insular development to selective integration. The corporate is reportedly in advanced discussions to license large language models from OpenAI and Anthropic to power an upgraded Siri offering capabilities that Apple’s in-house systems have yet to match. These models, including iterations of ChatGPT and Claude, would run on Apple’s own infrastructure, allowing for deeper OS-level integration without fully relinquishing control. Licensing means Apple skips the years-long grind of model training and tuning, but at the price of depending on rivals for core functionality.

That urgency extends to Apple’s other major bet: spatial computing. The corporate is developing not less than seven head-worn devices, including three Vision headsets and 4 smart glasses, in response to analyst Ming-Chi Kuo. A lighter, cheaper Vision Air is ready for 2027, shedding over 40% in weight and value by utilizing iPhone-grade chips and scaled-back materials. Apple’s first smart glasses will drop displays entirely, counting on AI, voice, audio, and gesture input for a more ambient, low-profile experience. A second-gen Vision Pro and full-color XR glasses are planned for 2028, continuing Apple’s push to guide in mixed reality hardware. Read more.
AI Talent Costs Are Hitting Escape Velocity
Silicon Valley’s AI talent war is heating up, and it’s not subtle. Researcher salaries have jumped into the stratosphere, with top-tier engineers now commanding $500,000 to $2 million annually. The arms race for brains is being bankrolled by billions in fresh capital.
One of the crucial aggressive latest players is Pondering Machines Lab (TML), a stealth startup founded in early 2025 by former OpenAI CTO Mira Murati. In response to federal H-1B filings, TML offers base salaries of $450,000 to $500,000, well above the averages at OpenAI ($292,115) and Anthropic ($387,500). These salaries don’t include potential equity or sign-on bonuses.
TML is currently focused on internal development, having paused latest applications. The corporate positions itself as constructing AI that’s more interpretable, customizable, and capable.

Image: Patrick T. Fallon / AFP
This escalating talent war is ready against a backdrop of massive capital infusions across the sector. Elon Musk’s xAI recently raised $10 billion in a combination of debt and equity to fund its Grok platform and construct out considered one of the world’s largest AI data centers, projecting $13 billion in annual expenditures. Meta, never one to be neglected of a talent tug-of-war, is reportedly flashing $100M+ packages and looking for $29B to bulk up its AI infrastructure. Forget lean startups. That is AI at Fortune 500 scale, where top minds are paid like hedge fund managers. Read more.
xAI Preps Grok 4 Rollout with Dual Models for Language and Code
xAI is gearing as much as launch Grok 4 through its developer console, with two distinct models surfaced within the platform’s source code: Grok 4 and Grok 4 Code.
Grok 4 is positioned because the core flagship, optimized for natural language, math, and reasoning tasks. It’s built as a high-performance generalist, designed to handle a large spectrum of inputs. Grok 4 Code is purpose-built for developers, offering code-aware support directly inside editors like Cursor. It might probably parse, debug, and reply to programming questions in context.
The API now supports text input, with vision and image generation features within the pipeline. The infrastructure suggests xAI is racing to satisfy demand with sharper tooling across use cases.
At the identical time, Grok is being tested for a second key use case: fact-checking. 𝕏 is piloting a system that lets Grok and other large language models generate Community Notes, that are explanatory fact-checks attached to user posts.
Introducing AI Note Author API 🤖 AI helping humans. Humans still in charge.
Starting today, the world can create AI Note Writers that may earn the flexibility to propose Community Notes. Their notes will show on X if found helpful by people from different perspectives — identical to
— Community Notes (@CommunityNotes)
7:35 PM • Jul 1, 2025
These AI-generated notes must go through the platform’s consensus-based approval system, designed to balance speed with editorial integrity. While the automation may scale moderation, experts caution that language models’ tendency to hallucinate and the danger of flooding the system could backfire. A recent paper advocates for a human-AI feedback loop, where LLMs assist slightly than replace human judgment. Read more.


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