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"describing how they had created an A.I. model to instantly translate the ancient glyphs. The team, led by a Google software engineer and an Assyriologist from Ariel University, trained the model on existing cuneiform translations using the same technology that powers Google Translate."

"The intriguing echo of Eliza in thinking about ChatGPT is that people regard it as magical even though they know how it works - as a "stochastic parrot" (in the words of Timnit Gebru, a well-known researcher) or as a machine for "hi-tech plagiarism" (Noam Chomsky). But actually we do not know the half of it yet - not the CO2 emissions incurred in training its underlying language model or the carbon footprint of all those delighted interactions people are having with it. Or, pace Chomsky, that the technology only exists because of its unauthorised appropriation of the creative work of millions of people that just happened to be lying around on the web? What's the business model behind these tools? And so on. Answer: we don't know."

"That is why we must demand transparency here, especially in the case of technology that uses human-like interfaces such as language. For any automated system, we need to know what it was trained to do, what training data was used, who chose that data and for what purpose. In the words of AI researchers Timnit Gebru and Margaret Mitchell, mimicking human behaviour is a "bright line" - a clear boundary not to be crossed - in computer software development. We treat interactions with things we perceive as human or human-like differently. With systems such as LaMDA we see their potential perils and the urgent need to design systems in ways that don't abuse our empathy or trust."

"Ellie may be a computer simulation, but she's incredibly perceptive. By reading the body language and vocal inflections of real live humans, she can engage in surprisingly meaningful exchanges, and even evoke emotional openness from her conversation partners. Her creators believe her receptivity to human emotional cues could revolutionize the field of mental health. Watching Ellie in action, it's not hard to see why."

"In response, the architects of the internet developed a kind of digital Esperanto: a common language that enabled data to travel across any network. In 1974, two Arpa researchers named Robert Kahn and Vint Cerf published an early blueprint. Drawing on conversations happening throughout the international networking community, they sketched a design for "a simple but very flexible protocol": a universal set of rules for how computers should communicate."

"Such powerful software is still several years away from being fully developed, if at all, and raises all sorts of ethical questions. But the potential applications-such as masterfully translating foreign languages, identifying objects in photos and directing self-driving cars through busy intersections-are so compelling that technology giants like Facebook and Google Inc. are investing heavily in artificial intelligence"

"The volunteer workforce that built the project's flagship, the English-language Wikipedia-and must defend it against vandalism, hoaxes, and manipulation-has shrunk by more than a third since 2007 and is still shrinking. ..."

"Cambridge, Cambridgeshire (fenews) August 18, 2016 - Known for Software development in Cambridge, Product Technology Partners has been catering the Software Development needs of its clients in a wide range of languages since 2000."

"Facebook enables advertisers to promote content to nearly 900,000 people interested in "vaccine controversies", the Guardian has found. Other groups of people that advertisers can pay to reach on Facebook include those interested in "Dr Tenpenny on Vaccines", which refers to anti-vaccine activist Sherri Tenpenny, and "informed consent", which is language that anti-vaccine propagandists have adopted to fight vaccination laws."

"He had discovered that human learning was communal and interactive. For a robot, the acquisition of language was abstract and formulaic. For us, it was embodied, emotive, subjective, quivering with life. The future of intelligence wouldn't be found in our machines, but in the development of our own minds."

"Automating teaching is an example of a task that would require artificial general intelligence (as opposed to narrow or specific intelligence). In other words, this is the kind of task that would require an AI that understands natural human language, can be empathetic towards emotions, plan, strategize and make impactful decisions under unpredictable circumstances."

"In the last year, Facebook adjusted some of the most fundamental rules about what gets posted on its platform, halting algorithmic recommendations of political groups, banning lies about vaccines and removing a number of high-profile figures for spreading misinformation and hate - including Donald Trump. But researchers say the social media platform is not enforcing those policies as effectively when it comes to misinformation in Spanish - a blind spot that may prove deadly as health lies spread through the most vulnerable populations during the global vaccine effort."

"This is the biggest concern. I can't overstate how big of a problem this is. I'd be the first that wishes I could wave a magic wand and have an easy solution where all of this could be solved. A teacher I know says there's just 5 percent or 10 percent of her kids in Mountain View, Calif., who are just checked out. She can't get them to show up. She can even see that their language has degraded because they haven't spent as much time with adults or peers in an academic setting."

"The paper, co-authored by researchers inside and outside Google, contended that technology companies could do more to ensure AI systems aimed at mimicking human writing and speech do not exacerbate historical gender biases and use of offensive language, according to a draft copy seen by Reuters."

"The Solomon Islands government is preparing to ban Facebook - an attempt, it says, to limit "abusive language" and "character assassination" but which critics argue is an attempt to curtail criticism of the government. "

"Second, there is the question of how we see ourselves. Human nature is a baggy, capacious concept, and one that technology has altered and extended throughout history. Digital technologies challenge us once again to ask what place we occupy in the universe: what it means to be creatures of language, self-awareness and rationality."

"Some have argued for much greater policing of content online, and companies like Facebook, YouTube, and Twitter have talked about hiring thousands to staff up their moderation teams.8 8. April Glaser, Want a Terrible Job? Facebook and Google May Be Hiring,Slate (Jan. 18, 2018), https://slate.com/technology/2018/01/facebook-and-google-are-building-an-army-of-content-moderators-for-2018.html (explaining that major platforms have hired or have announced plans to hire thousands, in some cases more than ten thousand, new content moderators).On the other side of the coin, companies are increasingly investing in more and more sophisticated technology help, such as artificial intelligence, to try to spot contentious content earlier in the process.9 9. Tom Simonite, AI Has Started Cleaning Up Facebook, But Can It Finish?,Wired (Dec. 18, 2018), https://www.wired.com/story/ai-has-started-cleaning-facebook-can-it-finish/.Others have argued that we should change Section 230 of the CDA, which gives platforms a free hand in determining how they moderate (or how they don't moderate).10 10. Gohmert Press Release, supra note 7 ("Social media companies enjoy special legal protections under Section 230 of the Communications Act of 1934, protections not shared by other media. Instead of acting like the neutral platforms they claim to be in order obtain their immunity, these companies have turned Section 230 into a license to potentially defraud and defame with impunity… Since there still appears to be no sincere effort to stop this disconcerting behavior, it is time for social media companies to be liable for any biased and unethical impropriety of their employees as any other media company. If these companies want to continue to act like a biased medium and publish their own agendas to the detriment of others, they need to be held accountable."); Eric Johnson, Silicon Valley's Self-Regulating Days "Probably Should Be" Over, Nancy Pelosi Says, Vox (Apr. 11, 2019), https:/

"After a decade or so of the general sentiment being in favor of the internet and social media as a way to enable more speech and improve the marketplace of ideas, in the last few years the view has shifted dramatically-now it seems that almost no one is happy. Some feel that these platforms have become cesspools of trolling, bigotry, and hatred.1 1. Zachary Laub, Hate Speech on Social Media: Global Comparisons, Council on Foreign Rel. (Jun. 7, 2019), https://www.cfr.org/backgrounder/hate-speech-social-media-global-comparisons.Meanwhile, others feel that these platforms have become too aggressive in policing language and are systematically silencing or censoring certain viewpoints.2 2. Tony Romm, Republicans Accused Facebook, Google and Twitter of Bias. Democrats Called the Hearing 'Dumb.', Wash. Post (Jul. 17, 2018), https://www.washingtonpost.com/technology/2018/07/17/republicans-accused-facebook-google-twitter-bias-democrats-called-hearing-dumb/?utm_term=.895b34499816.And that's not even touching on the question of privacy and what these platforms are doing (or not doing) with all of the data they collect."

"To create Discover Weekly, there are three main types of recommendation models that Spotify employs: Collaborative Filtering models (i.e. the ones that Last.fm originally used), which analyze both your behavior and others' behaviors. Natural Language Processing (NLP) models, which analyze text. Audio models, which analyze the raw audio tracks themselves."

"DATA LEVERAGE CAN be deployed through at least four avenues: direct action (for instance, individuals banding together to withhold, "poison," or redirect data), regulatory action (for instance, pushing for data protection policy and legal recognition of "data coalitions"), legal action (for instance, communities adopting new data-licensing regimes or pursuing a lawsuit), and market action (for instance, demanding large language models be trained only with data from consenting creators). "