⚡️ 2.39x Faster Thinking

Good Morning. Microsoft and Tsinghua University researchers might have found a breakthrough for quick-witted language models. But can speed come without a cost? Let’s dive in.

Today’s Highlights:

• JPMorgan bets on AI to outpace Wall Street

• Pentagon's push for AI-enabled drones stirs debate

• Formula 1 race rulings to get a tech boost

DEEP DIVE

Skeleton-of-Thought Speeds Up Language Model Responses

Researchers at Microsoft and Tsinghua University are pushing the limits of LLMs with their latest innovation called Skeleton-of-Thought (SoT), a fresh approach designed to significantly enhance the response times of LLMs such as GPT-4 and LLaMA.

Confronted with the challenge of sluggish LLM processing speeds, the research team's unique solution bypasses the complex model and system alterations, choosing instead to treat the LLMs as black boxes. This method dramatically improves the output efficiency without diving into the complexities of model architecture.

• SoT outpaces traditional augmentation strategies by focusing on organizing the output content, simplifying the production process.

• The two-staged pathway starts by forming a 'skeleton' answer, which mirrors human problem-solving strategies.

The evaluation results are striking: Using SoT led to speed-ups ranging from 1.13x to 2.39x without compromising the answer quality. These findings were corroborated across 12 different models covering a broad spectrum of domains such as coding, mathematics, writing, and roleplay, utilizing datasets like Vicuna-80.

However, speed isn't everything—the quality of responses is just as important. Metrics from FastChat and LLMZoo validate that SoT not only maintains but can improve the quality of answers, a vital attribute for any AI application where both efficiency and reliability are paramount.

While skeptics might wonder about the implications for AI development, SoT offers an exciting glimpse into a future where speed and smarts go hand in hand, further blurring the lines between algorithmic calculation and human-like reasoning.

Keep reading here.

PUNCHLINES

Bye Siri: ChatGPT's voice chat emerges from behind the paywall, putting Siri on the stand-by list.

Cold War, Colder Chips: AI chipmaker Graphcore freezes operations in China as US export rules bite.

Wall Street's New Algorithm: JPMorgan doubles down on AI, seeking to outsmart the stock market.

Virtual Vanity Fair: An agency's AI model may just be the cure for the headache caused by high-maintenance human influencers.

Deadly Keystrokes: Forget phishing—hackers can now guess your password by eavesdropping on your keystrokes with 95% accuracy.

TLDR

Rise of the 'Killer robots': The Pentagon is advancing towards AI-enabled drones capable of independently identifying and engaging targets. Already in development, these autonomous drones could revolutionize battlefield strategies against larger forces, notwithstanding heated debates over the moral repercussions of relinquishing human control in lethal military operations.

AI to assist Formula 1 officials in track rulings: The FIA plans to integrate Computer Vision to identify clear track limit violations during races, significantly cutting down on the number of manual reviews required and paving the way for a tech-driven future in race officiating.

Governance crisis at OpenAI: As OpenAI pivots towards a new board structure, balancing commercial interest with ethical tenets becomes critical. The company is challenged to incorporate diverse, critical thinkers on its board, especially in the wake of concerns surrounding biased AI and after a controversial reshuffling of board roles.

GPT-4 misleads in medical study simulation: A study leveraging GPT-4 created fake data favoring one corneal surgery over another, countering real-world evidence. The experiment exposed how AI could easily fabricate realistic data, raising alarms over research integrity and the potential for undetectable scientific fraud.

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