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Elon Musk says Twitter's blue check mark program will return on Friday, December 2nd with a new procedure to verify individual identities in order to resolve impersonation issues. Musk described the new manual authentication process as "painful, but necessary." Verified check marks will also be expanded with additional colors--gold for companies, grey for government entities, and the original blue for individual accounts.
As it turns out, offering so-called verified check marks for an $8 monthly subscription without actually verifying identities wasn't a brilliant idea. After Musk ignored warnings from Twitter's own trust and safety staff, the platform's paid Twitter Blue subscriptions rolled out and quickly resulted in some 'verified' accounts impersonating notable public figures and brands, driving away advertisers from the "high-risk" platform. Musk has since said that the company wouldn't relaunch Twitter Blue until "we're confident about significant impersonations not happening."
Musk had previously said that Twitter "will probably use different color check for organizations than individuals," adding: "All verified individual humans will have same blue check, as boundary of what constitutes 'notable' is otherwise too subjective." He also explained that individuals can have secondary tiny logo showing they belong to an org if verified as such by that org.”The Twitter CEO says he’ll offer a longer explanation about how everything will work at some point next week. Read more...
You know how you always dream of being able to control things with your mind? Well, it turns out we can do that now.
Researchers at OpenAI have made a neural network that learns by watching videos of people playing Minecraft. It's the first time anyone has created a bot that can craft diamond tools in the game, which usually takes good human players 20 minutes of high-speed clicking—or around 24,000 actions.
The result is a breakthrough for a technique known as imitation learning, in which neural networks are trained how to perform tasks by watching humans do them. The problem with existing approaches to imitation learning is that video demonstrations need to be labeled at each step: doing this action makes this happen, doing that action makes that happen, and so on. Annotating by hand in this way is a lot of work, and so such datasets tend to be small.
The team’s approach, called Video Pre-Training (VPT), gets around the bottleneck in imitation learning by training another neural network to label videos automatically. Read more...
AI is here and it's not going anywhere.
In 2018 at the World Economic Forum in Davos, Google CEO Sundar Pichai had something to say: “AI is probably the most important thing humanity has ever worked on. I think of it as something more profound than electricity or fire.” Pichai’s comment was met with a healthy dose of skepticism. But nearly five years later, it’s looking more and more prescient.
AI translation is now so advanced that it’s on the brink of obviating language barriers on the internet among the most widely spoken languages. College professors are tearing their hair out because AI text generators can now write essays as well as your typical undergraduate — making it easy to cheat in a way no plagiarism detector can catch. AI-generated artwork is even winning state fairs. A new tool called Copilot uses machine learning to predict and complete lines of computer code, bringing the possibility of an AI system that could write itself one step closer. DeepMind’s AlphaFold system, which uses AI to predict the 3D structure of just about every protein in existence, was so impressive that Science named it 2021’s Breakthrough of the Year.
While innovation in other technological fields can feel sluggish — as anyone waiting for the metaverse would know — AI is full steam ahead. The rapid pace of progress is feeding on itself, with more companies pouring more resources into AI development and computing power. Read more...
Binance has allocated another $1 billion to its Secure Asset Fund for Users (SAFU) just days after topping it up to $1 billion after its value fell as the crypto market declined.
The emergency insurance pot was established in 2018 to protect users' funds. The expansion was affirmed in an email to CoinDesk after Binance CEO Changpeng "CZ" Zhao on Friday tweeted the money had been allocated to the exchange's Industry Recovery Initiative, which aims to consider investment opportunities resulting from the collapse of firms such as Three Arrows Capital, Celsius and FTX.
Binance also said Aptos Labs and Jump Crypto, along with other prominent crypto companies joined the industry initiative and will contribute $50 million to the fund.
The recovery fund would be used to buy distressed crypto assets and support the industry. The crypto market has seen a massive decline since the start of the year, leading to several crypto firms going out of business. Read more...
The world economy is in the early stages of a profound transition from an industrial to a digital economy.
Industrial economies industrialized economic production using physical innovations, such as steam engines and factories. Such institutional technologies organize people and machines into high production. What the steam engine did for industry, the trust engine will do for society.
The fundamental factor of production that a digital economy economizes on is trust.
Blockchain is not a new tool. It is a new economic infrastructure that enables anyone, anywhere, to trust the underlying facts recorded in a blockchain, including identity, ownership and promises represented in smart contracts. These economic facts are the base layer of any economy. They generally work well in small groups – a family, village or small firm – but the verification of these facts and monitoring of how they change becomes increasingly costly as economic activity scales up.
Layers of institutional solutions to trust problems have evolved over perhaps thousands of years. These are deep institutional layers – the rule of law, principles of democratic governance, independence of bureaucracy etc. Next, there are administrative layers containing organisational structures – the public corporation, non-profits, NGOs and similar technologies of cooperation. Then we have markets – institutions that facilitate exchange between humans. Read more...
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