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Apple evaluated over 20 Large Language Models (LLMs)—including OpenAI's o1 and GPT-4o, Google's Gemma 2, and Meta's Llama 3—to assess their capacity for "true logical reasoning" versus whether their "intelligence" stemmed from "sophisticated pattern matching."

TODAY IN MORNING AI

• Major AI Flaw Discovered by Apple: Implications for Users and Developers

• Meta's chief AI scientist, dismissed existential concerns about AI

• TikTok announced plans to cut hundreds of jobs worldwide

• AI pioneer Yoshua Bengio expressed concerns about the risks of AI

• AI fun fact

  and more…

Read Time: 7 Minutes 04 Seconds

AI HEADLINES
TOP AI STORIES

Meta's chief AI scientist, Yann LeCun, dismissed existential concerns about AI as "complete BS," claiming that current systems are no more intelligent than a house cat.

TikTok announced plans to cut hundreds of jobs worldwide, citing a transition towards increased use of AI in its content moderation.

AI pioneer Yoshua Bengio expressed concerns about the risks of AI in a recent interview, warning that humanity may be on a path to "creating monsters that could surpass us."

A study from Sun Yat-sen University utilized Meta’s ESMFold protein-prediction tool to identify 70,500 new RNA viruses from environmental data.

Apple is reportedly preparing to release a lower-cost version of its Vision headset, priced at $2,000, compared to the $3,500 Vision Pro, which has faced lackluster sales.

AI DEVELOPMENT
Major AI Flaw Discovered by Apple: Implications for Users and Developers

Apple evaluated over 20 Large Language Models (LLMs)—including OpenAI's o1 and GPT-4o, Google's Gemma 2, and Meta's Llama 3—to assess their capacity for "true logical reasoning" versus whether their "intelligence" stemmed from "sophisticated pattern matching." The findings highlighted significant weaknesses.

Key Points:

LLMs' reasoning abilities are typically assessed using the popular benchmark test—GSM8K—but there's a chance these models answer correctly solely because they have been pre-trained on specific answers.

Apple introduced a new benchmark—GSM-Symbolic—that tested the models by altering variables in the questions (e.g., adding irrelevant details or changing names/numbers). The results showed a decline in performance across all LLMs.

Consequently, Apple concluded that there is “no formal reasoning” in LLMs; their responses are better explained by sophisticated pattern matching. Even minor changes, such as altering a name, led to a 10% drop in performance.

Why This Matters: If LLMs depend on pattern matching rather than true logical reasoning, they may not be reliable for AI applications that require consistent and accurate reasoning in real-world scenarios. It will be intriguing to see how Apple, as a competitor to Google, Meta, and OpenAI (despite their recent partnership), addresses the implications of this critical study.

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AI DESIGNS

 Amidst the whirring chaos of a robotic city, a lone android struggles to maintain balance, grappling with the weight of expectations and the constant juggling of tasks as it falls on its knees, tired.

AI FUN FACT
DID YOU KNOW?

AI algorithms on social media platforms can analyze user behavior and preferences to tailor content specifically for you? This means that the posts, ads, and recommendations you see are often influenced by sophisticated machine learning models designed to keep you engaged and interacting with the platform!

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