GPT-3 large language model

GPT-3 (Generative Pre-trained Transformer 3) is a language model that uses deep learning to generate natural, human-like language from text prompts. 

Developed by OpenAI, GPT-3 has 175 billion parameters, ten times more than any previous model. It was released as a beta in May 2020. 

Reaction

GPT-3 has won fulsome praise from technology professionals, commentators, scientists, and philosophers for the quality of text it produces, and its ability to synthesise massive amounts of content. 

MIT Technology Review described it as 'shockingly good' and able to generate 'amazing human-like text on demand'. It is, according to the National Law Review, 'a glimpse of the future'. 

But New York Times technology columnist Farhad Manjoo described GPT-3 as 'at once amazing, spooky, humbling, and more than a little terrifying,' and NYU professor Gary Marcus dismissed it as 'a fluent spouter of bullshit, but even with 175 billion parameters and 450 gigabytes of input data, it’s not a reliable interpreter of the world. ' 

Even OpenAI CEO Sam Altman admitted the tool has 'serious weaknesses and sometimes makes very silly mistakes.'

Limitations

• Accuracy/reliability: lack of common sense, cut-and-paste jobs, 

• Bias/discrimination: race, religion (anti-Muslim bias)

• Safety: AI dungeon filter

• Mis/disinformation: short-form

Risks

• Business model

• Competition/price fixing

• Dual/multi-use - Koko mental health experiment

• Environment: emissions

Transparency

OpenAI researchers point out in a research paper accompanying the GPT-3's release

• Governance

• Black box