"SOUTH OF THE Huai river few geese can be seen through the rain and snow." In classical Chinese this verse is a breakthrough--not in literature but in computing power. The line, composed by an artificial intelligence (AI) language model called Wu Dao 2.0, is indistinguishable in metre and tone from ancient poetry. The lab that built the software, the Beijing Academy of Artificial Intelligence (BAAI), challenges visitors to its website to distinguish between Wu Dao and flesh-and-blood 8th-century masters. Anecdotal evidence suggests that it fools most testers.
Google's quantum supremacy experiment used 53 noisy qubits to demonstrate it could perform a calculation in 200 seconds on a quantum computer that would take 10,000 years on the largest classical computer using existing algorithms. This marks the beginning of the Noisy Intermediate-Scale Quantum (NISQ) computing era. In the coming years, quantum devices with tens-to-hundreds of noisy qubits are expected to become a reality. Quantum computing relies on properties of quantum mechanics to compute problems that would be out of reach for classical computers. A quantum computer uses qubits.
These projects emulate the work that these professionals do throughout industry. Machine learning (ML) is often a project component in all three areas but its use depends on the role. Data Scientists often use ML to uncover insights to drive a business or model users to improve data products. Data Engineers solve engineering challenges to apply ML methods when the amount of data is massive and requires distributed computation. And, as mentioned in our post on "How AI Careers Fit into the Data Landscape", AI focuses on understanding core human abilities and designing algorithms, which often have a ML component, to emulate these processes.
Lately, I've been thinking and reading a lot about consciousness and how the human mind works. A question that emerges all the time is whether machines can emulate human thought. An even more interesting one is whether consciousness (a subjective experience) can arise from a machine, but I'll leave that discussion for a future post (I'll need 20 more years to think about that before I can write about it). So, how far are we from _behaviorally _imitating a human? Truth is, we achieved a lot in the past 5 years (see AlphaGo, OpenGPT-2, OpenAI Jukebox, Tesla Autopilot, Alphastar, OpenAI Dota2 Team, OpenAI API), but we're still quite not there.
Artificial Intelligence will change lives. It will change the economy. It will change the world. You hear about it on the news and you see Google and other tech companies come out with this ridiculously advanced products which make you think "Oh god, in 20 years I'll have a terminator roaming around in my neighborhood". Now, while I can't say that that won't happen I can at least say that this is not at all the case with today's technology.