Two great resources for those wanting to track the when and the how of AI progress.
AI Timelines is the discussion of how long until various major milestones in AI progress are achieved, whether it’s the timeline until a human-level AI is developed, the timeline until certain benchmarks are defeated, the timeline until we can simulate a mouse-level intelligence, or something else.
AI Takeoff refers to the process of an Artificial General Intelligence going from a certain threshold of capability (often discussed as “human-level”) to being super-intelligent and capable enough to control the fate of civilization. There has been much debate about whether AI takeoff is more likely to be slow vs fast, i.e., “soft” vs “hard”.
Daily Archives: March 31, 2023
Sparks of Artificial General Intelligence:Early experiments with GPT-4
Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. The latest model developed by OpenAI, GPT-4 [Ope23], was trained using an unprecedented scale of compute and data. In this paper, we report on our investigation of an early version of GPT-4, when it was still in active development by OpenAI. We contend that (this early version of) GPT4 is part of a new cohort of LLMs (along with ChatGPT and Google’s PaLM for example) that exhibit more general intelligence than previous AI models. We discuss the rising capabilities and implications of these models. We demonstrate that, beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. Moreover, in all of these tasks, GPT-4’s performance is strikingly close to human-level performance, and often vastly surpasses prior models such as ChatGPT. Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. In our exploration of GPT-4, we put special emphasis on discovering its limitations, and we discuss the challenges ahead for advancing towards deeper and more comprehensive versions of AGI, including the possible need for pursuing a new paradigm that moves beyond next-word prediction. We conclude with reflections on societal influences of the recent technological leap and future research directions. Read More
Songwriting at the Dawn of AI: When Machines Can Write, Who Is the Artist?
The United States Copyright Office recently issued new guidelines regarding copyright applications for works created with artificial intelligence tools. The new rules recognize that work made with both AI input and human creation can be eligible for copyright protection, but any part of it that is entirely made by AI is not eligible. Which is to say, copyright protections can extend only to work that is attributable to human authorship.
“If a work’s traditional elements of authorship were produced by a machine, the work lacks human authorship and the Office will not register it,” the report states. “For example, when an AI technology receives solely a prompt from a human and produces complex written, visual, or musical works in response, the ‘traditional elements of authorship’ are determined and executed by the technology—not the human user.” The report hypothesizes that a work that creatively combines AI-generated elements into something new or AI-generated work that an artist then heavily modifies after the fact would indeed be eligible. Read More
How a tiny company with few rules is making fake images go mainstream
Midjourney, the year-old firm behind recent fake visuals of Trump and the pope, illustrates the lack of oversight accompanying spectacular strides in AI
The AI image generator Midjourney has quickly become one of the internet’s most eye-catching tools, creating realistic-looking fake visuals of former president Donald Trump being arrested and Pope Francis wearing a stylish coat with the aim of “expanding the imaginative powers of the human species.”
But the year-old company, run out of San Francisco with only a small collection of advisers and engineers, also has unchecked authority to determine how those powers are used. Read More
Deep Learning Is Hitting a Wall
What would it take for artificial intelligence to make real progress?
Let me start by saying a few things that seem obvious,” Geoffrey Hinton, “Godfather” of deep learning, and one of the most celebrated scientists of our time, told a leading AI conference in Toronto in 2016. “If you work as a radiologist you’re like the coyote that’s already over the edge of the cliff but hasn’t looked down.” Deep learning is so well-suited to reading images from MRIs and CT scans, he reasoned, that people should “stop training radiologists now” and that it’s “just completely obvious within five years deep learning is going to do better.”
Fast forward to 2022, and not a single radiologist has been replaced. Rather, the consensus view nowadays is that machine learning for radiology is harder than it looks; at least for now, humans and machines complement each other’s strengths. Read More
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