How would an AI writing program start an article on the future of AI writing? Well, there's one easy way to find out: I used the best known of these tools, OpenAI's GPT-3, to do the job for me. Using GPT-3 is disarmingly simple. You have a text box to type into and a menu on the side to adjust parameters, like the "temperature" of the response (which essentially equates to randomness). You type, hit enter, and GPT-3 completes what you've written, be it poetry, fiction, or code. I tried inputting a simple headline and a few sentences about the topic, and GPT-3 began to fill in the details. It told me that AI uses "a series of autocomplete-like programs to learn language" and that these programs analyze "the statistical properties of the language" to "make educated guesses based on the words you've typed previously."

In an internal memo sent by Jeff Dean, head of Google's research division to employees stated Google Health will no longer function as a unit. Formed in 2018, Google Heath which included artificial-intelligence research teams Google Brain and DeepMind, as well as health teams from Nest Labs, the connected-home company Google bought in 2014. In addition, Google Health's clinician team will report to Jeff Dean and its artificial intelligence team will report to Google's search and AI team. Moving forward the Google Health name will encompass all our health initiatives," tweeted Jeff Dean.

Artificial intelligence is already capable of doing some incredibly useful things, like predicting flooding, diagnosing disease, and instantly translating languages. Advances in neural networks coupled with enormous computational power have allowed tech companies to create incrementally smarter AI models over the last decade. Jeff Dean, Google's AI chief, thinks we're just scratching the surface. Speaking at the TED conference in Monterey, California, this week, he revealed that Google is developing a nimble, multi-purpose AI that can perform millions of tasks. Called Pathways, Google's solution seeks to centralize disparate AI into one powerful, all-knowing algorithm.

Artificial intelligence is already capable of doing some incredibly useful things, like predicting flooding, diagnosing disease, and instantly translating languages. Advances in neural networks coupled with enormous computational power have allowed tech companies to create incrementally smarter AI models over the last decade. Jeff Dean, Google's AI chief, thinks we're just scratching the surface. Speaking at the TED conference in Monterey, California, this week, he revealed that Google is developing a nimble, multi-purpose AI that can perform millions of tasks. Called Pathways, Google's solution seeks to centralize disparate AI into one powerful, all-knowing algorithm.

Google has fired Margaret Mitchell, co-lead of the ethical AI team, after she used an automated script to look through her emails in order to find evidence of discrimination against her coworker Timnit Gebru. The news was first reported by Axios. Mitchell's firing comes one day after Google announced a reorganization to its AI teams working on ethics and fairness. Marian Croak, a vice president in the engineering organization, is now leading "a new center of expertise on responsible AI within Google Research," according to a blog post. Mitchell joined Google in 2016 as a senior research scientist, according to her LinkedIn. Two years later, she helped start the ethical AI team alongside Gebru, a renowned researcher known for her work on bias in facial recognition technology.

Deep learning is that form of AI which excels in incorporating the human brain that ultimately aids in better decision-making capabilities. There are numerous applications that rely on deep learning. One such application that garnered attention from everyone across is its incorporation in AI chips. Jeff Dean, an American computer scientist and also Google's brain director had mentioned how Google would be using artificial intelligence to advance its internal development of custom chips about a year ago. This would ultimately pave the way for accelerating its software.

Deep learning is that form of AI which excels in incorporating the human brain that ultimately aids in better decision-making capabilities. There are numerous applications that rely on deep learning. One such application that garnered attention from everyone across is its incorporation in AI chips. Jeff Dean, an American computer scientist and also Google's brain director had mentioned how Google would be using artificial intelligence to advance its internal development of custom chips about a year ago. This would ultimately pave the way for accelerating its software.

Google is making changes to how it reviews papers following an internal revolt over the company's controversial practices. Leading AI ethics researcher Timnit Gebru was fired from Google in December last year after sending an email to colleagues which criticised the company's practices. Gebru claims Google blocks the publication of papers that may cause criticism of the company's work; including her most recent which questioned whether language models can be too big, who benefits from them, and whether they can increase prejudice and inequalities. In an email to employees following Gebru's firing, Jeff Dean, Head of Google Research, said: "Papers often require changes during the internal review process (or are even deemed unsuitable for submission). Unfortunately, this particular paper was only shared with a day's notice before its deadline -- we require two weeks for this sort of review -- and then instead of awaiting reviewer feedback, it was approved for submission and submitted. A cross-functional team then reviewed the paper as part of our regular process and the authors were informed that it didn't meet our bar for publication and were given feedback about why."

AI and ML systems have advanced in both sophistication and capability at a staggering rate in recent years. They can now model protein structures based only on the molecule's amino-acid sequence, create poetry and text on par with human writers -- even spot specific individuals in a crowd (assuming their complexion is sufficiently light). But for as impressive as these feats of computational prowess are, the field continues to struggle with a number of fundamental moral and ethical issues. A facial recognition system designed to identify terrorists can just as easily be leveraged to monitor peaceful protesters or suppress ethnic minorities, depending on how it is deployed. What's more, the development of AI to date has been largely concentrated in the hands of just a few large companies such as IBM, Google, Amazon and Facebook, as they're among the few with sufficient resources to pour into its development.

Gebru, an alumni of the Stanford Artificial Intelligence Laboratory, is one of the leading voices in the ethical use of artificial intelligence. She is well-known for her work on a landmark study in 2018 that showed how facial recognition software misidentified dark-skinned women as much as 35% of the time, whereas the technology worked with near precision on white men. She has also been an outspoken critic of the lack of diversity and unequal treatment of Black workers at tech companies, particularly at Alphabet Inc.'s Google, and said she believed her dismissal was meant to send a message to the rest of Google's employees not to speak up. Platformer received the email Gebru sent; she herself did not have access to her account after Google terminated her. It is published in full below.