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THE DAILY BRIEF

FRIDAY, AUGUST 14, 2026

■ TOP STORY

US AUTHORIZES PRIVATE SECTOR CYBERATTACKS

A Trump administration memo marks the first time the U.S. government has formally authorized private companies to conduct cyberattacks on its behalf, signaling a major shift in how the nation approaches offensive cyber operations.

► WHY IT MATTERS: This privatization of offensive cyber capabilities creates accountability gaps and raises questions about rules of engagement when non-state actors conduct government-sanctioned attacks.

4 SOURCES
2.

OPENAI ULTRAFAST API HITS 750 TOKENS/SEC

OpenAI is launching a preview of Ultrafast, a new API tier powered by Cerebras hardware that runs its latest GPT-5.6 Sol model up to 14 times faster with 750 tokens-per-second output, targeting enterprise users who need speed at scale.

Real-time AI inference at this speed fundamentally changes what's economically viable for production applications, potentially unlocking use cases previously blocked by latency.

11 SOURCES
3.

GOOGLE SLASHES GEMINI PRICES BY 50%

Google released Gemini 3.7 Flash with improved coding capabilities while cutting prices in half compared to its three-week-old predecessor, intensifying price competition in the LLM market.

Rapid model iteration cycles and aggressive pricing from market leaders are compressing both development timelines and margins across the AI industry.

4.

DATABRICKS HITS $190B AT $7B REVENUE RUN RATE

Databricks raised another $5B in six months at a $190B valuation (up from $134B), now claiming $7B in annualized revenue—demonstrating investor appetite for AI infrastructure plays that show profitable unit economics.

A data/AI infrastructure company reaching $7B revenue at a $190B valuation establishes the infrastructure layer as the most valuable tier in the current AI stack.

3 SOURCES
5.

AMD ACQUIRES TAALAS FOR HARDCODED AI CHIPS

AMD acquired Taalas, a Toronto startup that embeds model weights directly into silicon for inference acceleration, achieving over 16,000 tokens-per-second performance—locking each chip to a single model but dramatically improving speed.

Hardware vendors are moving toward model-specific silicon optimization, fragmenting the chip landscape but offering orders of magnitude performance gains that software alone cannot match.

6 SOURCES

■ COMPILED BY THE NEWSROOM ■ SOURCES: 15 RSS FEEDS

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