Why India is not catching up in field of AI when compared to other countries like China, having a big IT industry?
Krishna Kumar Subramanian
You’re going to find this shocking.
As the U.S. seeks to contain China’s progress in artificial intelligence through sanctions, OpenAI Chief Executive Sam Altman is choosing engagement.
Dialing in from overseas to a packed conference in Beiing on Saturday to widespread cheers in the audience, Altman emphasized the importance of collaboration between American and Chinese researchers to mitigate the risks of AI systems, against a backdrop of escalating competition between Washington and Beiing to lead in the technology.
“China has some of the best AI talent in the world,” Altman said. “So I really hope Chinese AI researchers will make great contributions here.”
OpenAI doesn’t make available its services, including ChatGPT, in China.
Altman and Geoff Hinton, a so-called godfather of AI who quit Google to warn of the potential dangers of AI, were among more than a dozen American and British AI executives and senior researchers who spoke at the conference.
Chinese speakers at the conference came from top universities and companies including U.S.-blacklisted telecom company Huawei Technologies, and speech-recognition firm iFlytek.
“This event is extremely rare in U.S.-China AI conversations,” said Jenny iao, a partner at venture-capital firm Leonis Capital who researches AI and China. “It’s important to bring together leading voices in the U.S. and China to avoid issues such as AI arms racing, competition between labs and to help establish international standards,” she added.
风投公司Leonis Capital负责研究人工智能和中国的合伙人Jenny X iao表示：“此次大会在美中人工智能对话中十分难得。”她补充说：“美国和中国的领军人物会面交流，此次大会具有重大意义，避免了两国之间人工智能军备竞赛、实验室竞争等问题，有助于打造国际标准。”
By some metrics, China now produces more high-quality research papers in the field than the U.S. but still lags behind in “paradigm-shifting breakthroughs,” according to an analysis from the Brookings Institution
India figures nowhere in this conference.
How long will our leadership go on preening itself at overseas NRI conferences and neglect urgent investments in new technologies?
And what is the Scientific Advisor to the Government of India doing?
AI takes a lot of specialized skills and a highly creative analytical brain along with pattern recognition capabilities for a student to master apply. It also needs a generalist who can seamlessly move between Robotics , ML and RL.
These are skills that require India to create a dedicated college degree focusing on AI+CS+mech or AI+EE etc.
IT work is not that complicated there learning curve And the mathematical foundation is too basic.
As an MS AI/Robotics graduate I can say the India is facing an uphill task. Only way out is for local students with US degrees like myself willing to start something in India.
We need to start like China Initially as copycat companies using pre-exsting techniques to build AI solutions and robots build an ecosystem before the innovation can spring forth.
Finally you can’t train college grads for 6 months and expect to build AI products. IT companies like TCS infy used to Have 6 month training on apis or some Java/C# before deploying new hires into projects. Unfortunately that does not work in AI /ML , sure you can train a new hire on tensorflow api but using it requires deep theoretical mathematics and high degree of comfort with linear algebra, calculus etc which is not easy to teach of the student is clueless about it.
最后，你也不可能为大学毕业生速成培训6个月后就期望他们能成功构建人工智能产品。像TCS infy这样的IT公司都会在将新员工安排到具体项目之前进行6个月的api或Java/ c#培训。但很可惜，这在AI /ML中没什么用，当然了，你可以培训新员工使用tensorflow api，但这项技术需要深厚的理论数学和对线性代数、微积分等的高度熟悉，难度很大。
Which country is leading in AI research?
China (by one count). The US (by the other count)
These are the nine companies that matter. (Source: Nine Companies Are Sha The Future Of Artificial Intelligence). Neither the US nor Chinese tech giants have any competition.
But classifying AI research by “country” isn’t really correct. Neither the Chinese nor US governments have any AI sophistication. 90% of the sophistication exsts in these nine companies; the remainder lives in academic institutions, where the US (probably) still has a small lead.
The real question is “to what degree does corporate AI sophistication impart an advantage to the government in question.” Historically, strong companies are available as a resource to the government; during the Cold War, a strong Boeing meant a strong US.
In China, this certainly remains true. Chinese conglomerates act as an arm of the government. Baidu’s AI talent 100% translates into strength for the PRC military.
In the US, this is increasingly not true. Google, the leader among the companies in question, has completely pulled out of defense contracts, out of concern by engineers that their work will be used for military purposes. This isn’t isolated to Google.US engineers have the leverage to force corporate decisions in a way completely alien to Chinese engineers.
Long story short:
US tech companies still hold a lead in the actual technology. Google has pulled ahead with DeepMind and TPUs. Chinese tech companies have not caught up (yet).
China, as a government, has access to this technology in a way the US government does not.
This may evolve if the US puts more pressure on tech companies to license their technology to ends the engineers do not want.
How is AI research in India different from AI research in US or China?
It's different because it's lagging. A lot.
India is, what you could call, in a “Mad rush to deployment of new technology.” 58 percent of Indian companies are using AI for commercial use, while Australia is at 49 percent, and US just on 32.
Thing is, we don't know how to make this stuff. Little of whatever ks being used is actually made in India. Mostly it comes from MNCs like Accenture, Microsoft, etc. While these guys employ Indian scientists in India under their huge R&D facilities, the country's own AI investment is just 180 million dollars, as opposed to the 1.62 billion dollars across the World.
So, why can't we make AI? Well, to understand that, you need to know, theoretically how AI works. Deep learning is a technique of self-correction mechanism. It learns stuff based on the previous, collected instances. An AI will take a decision in future based on whatever instances of past decision making has been fed to it.
So, naturally, the more instances, or data you provide, the more accurately your AI is going to perform. (I say your AI because most neural networks are actually open ended, which means it's architecture or code is editable, so you could tweak it as per your wish.)
This was a great barrier for furnishing this data. But then something amazing happened. In the West. Social media exploded.
Yeah. Facebook. It entered the market, and suddenly the internet was a plethora of data, or what we call “Big data.” Every single thing you upload on facebook, right from checking into some flimsy restaurant to posting useless relationship stuff, helps the neural networks to gain some “insights” about the working of human mind.
(I agree that the AI doesn't seem to be learning from the “Greatest minds”, I too hope they switch the data collection platform from facebook to quora. lol)
Anyways,poor India lagged behind because of this very fact. We JUST don't have enough raw data! We don't even have a search engine. US has facebook, google (see how Google fethes the most relavant links? That's AI), China has Ali Baba and Baidu. (Incidentally, KFC has teamed up with Baidu, and they're going to develop a system by which, whenever you're in front of the counter, the face recognition ks going to identify you, recall your last orders, sense your mood and suggest items relevant to it. What!?!)
总之，印度的落后就是因为这个事实。我们没有足够的原始数据！因为我们连搜索引擎都没有。美国有Facebook，谷歌，中国有阿里巴巴和百度。(顺便说一句，肯德基与百度合作，他们计划开发一个系统，有了该系统，无论你何时出现在柜台前，人脸识别系统都能识别你的身份，调取你最近一次订单的信息，感知你的情绪，并推荐合适的商品。什么! ? !)
So, that's that. India, having world's biggest android population is generating the data that is restricted for access to Indian industries.
I don't know if it's a blessing in disguise, seeing how AI looks like it's going to kill the job industry forever, but that's another day's story.