GPT-4 Was the Biggest Disappointment Ever

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GPT-4 Was the Biggest Disappointment Ever …Despite it performing better than ChatGPT (based on GPT-3.5). Reason: The company deliberately decided not to reveal any specifics, like the parameter size or architecture, about the model. However, an AI researcher recently speculated on the inner workings of GPT-4, revealing why OpenAI chose to hide this information — it’s quite disappointing. Speaking about the potential size of the model, OpenAI chief Sam Altman famously stated that “people are begging to be disappointed, and they will be.”  Rumours, ironically started by Lex Friedman, ahead of the model’s launch suggested that it would have trillions of parameters and be the best thing that the world has ever seen. However, the reality is, in the process of making GPT-4 better than GPT-3.5, OpenAI might have bitten off more than it can chew.  World-renowned hacker and software engineer, George Hotz, recently appeared on a podcast speculating about the architectural nature of GPT-4. Hotz stated that the model might be a set of eight distinct models, each featuring 220 billion parameters. This speculation was later confirmed to be true by Soumith Chintala, the co-founder of PyTorch.  While this puts the parameter size of GPT-4 at 1.76 trillion, the notable part is that all of these models don’t work at the same time. Instead, they are deployed as a mixture of expert architecture.  Hotz also speculated that the model may be relying on the process of iterative inference for better output. In this process, the output or inference result of the model is refined through multiple iterations.  This method also might allow GPT-4 to get inputs from each of its expert models, which could reduce hallucinations. Hotz stated that this process might be done 16 times, which would vastly increase the operating cost of the model. Many likened this approach to the old trope of three kids in a trenchcoat masquerading as an adult. Many have equated GPT-4 to be 8 GPT-3s in a trench coat, trying to pull the wool over the world’s eyes.  If you enjoyed reading this, check out the complete story here.  Rethinking Chatbot Interaction  When Google introduced its search engine in 1996, nobody had a clue about the perfect way to use it. Some would begin with a casual "hi" or "hello" before posing their query, while others would simply insert a word or sentence to search. Cut to the present, not much has changed. Humans have become so used to typing into search engine and messaging app interfaces that conversing with AI, in the same manner, seemed like a natural transition.  Is it really how humans converse in reality if we are aiming at AGI? Read to find out.  Resurrecting Dead Children  Generative AI is now being used to tell true crime stories with visuals and the real faces of deceased children narrating what they underwent while using actual images of real psychopaths and murderers. Trigger warning: It’s creepy and nerve-wracking.  Rody Marie, a little girl gruesomely killed by her grandmother in 2018, is now making the rounds on the internet with generative AI being used to exploit her horrific story. Read the complete story here.  Google I/O Connect Google I/O happened in India this week, and it was a carbon copy of the Google I/O, San Francisco — beautiful Bengaluru weather being a bonus. At this event, Google played a perfectly responsible parent of the AI world by making sure that every announcement it made had a “responsible AI” resonance.  Check out all the hits and misses from the Google I/O Connect event here. Here’s a glimpse of everything that was announced: TAUSIF ALAM & AMIT RAJA NAIK Friday, Jun 30, 2023 | Was this email forwarded to you? Sign up here DOWNLOAD OUR MOBILE APP Stay Connected info@analyticsindiamag.com © 2023 Analytics India Magazine

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