Elon Musk, a famous person who makes cool things like electric cars and rockets, says his company's new computer brain called Grok 2 is going to be better than other big companies' computer brains. This means that the new computer brain can do more things and understand people better. He said it will be ready next week for people to use. Read from source...

1. The article is based on a tweet by Elon Musk that has no concrete evidence or source to back up his claim that Grok 2 will exceed current AI models on all metrics. This is a classic example of a sensational headline designed to attract attention and generate clicks, without providing any substance or credibility.

2. The article compares Grok 2 to other AI models that have not been officially released yet, such as OpenAI's GPT-4 and Anthropic's Claude 3. This is a highly speculative and unfair comparison, as it assumes that these future models will perform worse than Grok 2, without considering the possible advancements or improvements they might have over Grok 1.5 or other existing models.

3. The article uses subjective terms like "reasoning", "capabilities", "understanding context", and "more" to describe the alleged advantages of Grok 2 over other AI models, without providing any specific examples or data to support these claims. This is a vague and misleading way of presenting information, as it does not allow the reader to evaluate the actual performance or quality of Grok 2 in comparison to its competitors.

4. The article mentions xAI's announcement of a major update to Grok with improvements across various metrics, but does not provide any details or sources for this claim either. This is another instance of relying on unverified information and hearsay, without conducting any independent research or verification.

5. The article quotes xAI's statement that "Grok-1.5 is better than OpenAI's GPT-3" in terms of coding and math-related tasks, but does not mention how this comparison was made or what criteria were used to measure the performance of these models. This is a selective and misleading use of information, as it ignores the potential strengths or weaknesses of other AI models that might excel in different domains or tasks than coding and math.