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These five AI developments will shape 2021 and beyond



The year 2020 was profoundly challenging for citizens, companies, and governments around the world. As covid-19 spread, requiring far-reaching health and safety restrictions, artificial intelligence (AI) applications played a crucial role in saving lives and fostering economic resilience. Research and development (R&D) to enhance core AI capabilities, from autonomous driving and natural language processing to quantum computing, continued unabated.  

Baidu was at the forefront of many important AI breakthroughs in 2020. This article outlines five significant advances with implications for combating covid-19 as well as transforming the future of our economies and society.

1. AI and vaccine development

The trend—and why it matters. It typically takes years, if not decades, to develop a new vaccine. But by March 2020, vaccine candidates to fight covid-19 were already undergoing human tests, just three months after the first reported cases. The record speed of vaccine development was partly thanks to AI models that helped researchers analyze vast amounts of data about coronavirus.

There are tens of thousands of subcomponents to the outer proteins of a virus. Machine learning models can sort through this blizzard of data and predict which subcomponents are the most immunogenic—i.e., capable of producing an immune response—and thereby guide researchers in designing targeted vaccines. The use of AI in vaccine development may revolutionize the way all vaccines are created in the future.

Baidu’s innovations. In February, Baidu opened its LinearFold AI algorithm for scientific and medical teams working to fight the virus. LinearFold predicts the secondary structure of the ribonucleic acid (RNA) sequence of a virus—and does so significantly faster than traditional RNA folding algorithms. LinearFold was able to predict the secondary structure of the SARS-CoV-2 RNA sequence in only 27 seconds, 120 times faster than other methods. This is significant, because the key breakthrough of covid-19 vaccines has been the development of messenger RNA (mRNA) vaccines. Instead of conventional approaches, which insert a small portion of a virus to trigger a human immune response, mRNA teaches cells how to make a protein that can prompt an immune response, which greatly shortens the time span involved in development and approval. 

To support mRNA vaccine development, Baidu later developed and released an AI algorithm for optimizing mRNA sequence design called LinearDesign, which aims to solve the problem of unstable and unproductive mRNA sequences in candidate vaccines.  

In addition to opening up access to LinearFold and LinearDesign for researchers around the world, Baidu also formed a strategic partnership with the National Institute for Viral Disease Control and Prevention, part of the Chinese Center for Disease Control and Prevention. Following an outbreak at Beijing’s Xinfadi market in June, Baidu’s AI technology allowed authorities to complete genome sequencing of the coronavirus strain within 10 hours, helping curb the outbreak. In December, Baidu unveiled PaddleHelix, a machine learning-based bio-computing framework aimed at facilitating the development of vaccine design, drug discovery, and precision medicine.

2. Fully automated driving and the rollout of robotaxis

The trend—and why it matters. Autonomous driving technology continued to mature in 2020, with the industry’s leading companies testing driverless cars and opening up robotaxi services to the public in various cities. Fully automated driving, which enables rides without a human safety driver on board, will be necessary for the scalability and commercialization of autonomous driving.

Baidu’s innovations. Over the past year, Baidu launched the Apollo Go Robotaxi service in the Chinese cities of Changsha, Cangzhou, and Beijing—including in busy commercial areas—becoming the only company in China to start robotaxi trial operations in multiple cities.

These developments are a result of Baidu’s continuous innovation in developing AI systems that can safely control a vehicle in complex road conditions and solve the majority of possible issues on the road, independent of a human driver.

At Baidu World 2020, its annual technology conference, Baidu also demonstrated its fully automated driving capability—where the AI system drives independently without an in-vehicle safety driver. To support fully automated driving, Baidu developed the 5G Remote Driving Service, a safety measure whereby remote human operators can take control of a vehicle in the event of an exceptional emergency. Baidu’s achievement of fully automated driving, and the rollout of its robotaxis, suggests a positive outlook for the commercialization of the technology in the near future.

Source: Baidu

3. Applied natural language processing

The trend—and why it matters. In 2020, natural language systems became significantly more advanced at processing aspects of human language like sentiment and intent, generating language that aligns with human speaking and writing patterns, and even visual understanding, meaning the capability to express understanding about an image through language. These natural language models are powering more accurate search results and more sophisticated chatbots and virtual assistants, leading to better user experiences and creating value for businesses.

Baidu’s innovations. Baidu released a new multiflow sequence framework for language generation called ERNIE-GEN. By training the model to predict semantically complete blocks of text, ERNIE-GEN performs at an elite level across a range of language generation tasks, including dialogue engagement, question generation, and abstractive summarization.

Baidu’s vision-language model ERNIE-ViL also achieved significant progress in visual understanding, ranking first on the VCR leaderboard, a dataset of 290,000 questions built by the University of Washington and the Allen Institute for AI, that aims to test visual understanding ability. ERNIE-ViL also achieved state-of-the-art performance on five vision-language downstream tasks. Visual understanding lays the foundation for computer systems to physically interact in everyday scenes, as it involves both understanding visual content and expressing it through language. It will be crucial for improving the quality of human-machine interaction.

4. Quantum computing

The trend—and why it matters. Quantum computing made significant inroads in 2020, including the Jiuzhang computer’s achievement of quantum supremacy. This carries significance for AI, since quantum computing has the potential to supercharge AI applications compared to binary-based classical computers. For example, quantum computing could be used to run a generative machine learning model through a larger dataset than a classical computer can process, thus making the model more accurate and useful in real-world settings. Advanced technologies such as deep learning algorithms are also playing an increasingly critical role in the development of quantum computing research. 

Baidu’s innovations. Baidu achieved a number of technical breakthroughs in 2020 that promise to bridge AI and quantum computing. In May, Baidu launched Paddle Quantum, a quantum machine learning development toolkit that can help scientists and developers quickly build and train quantum neural network models and provide advanced quantum computing applications. The open-source toolkit both supports developers building quantum AI applications, and helps deep learning enthusiasts develop quantum computing. In September, Baidu entered cloud-based quantum computing with the launch of Quantum Leaf, which provides quantum development kits such as QCompute, and can shorten the life cycle of quantum programming and help realize a ‘closed-loop’ quantum tool chain.

Source: Baidu

5. AI chips

The trend—and why it matters. AI hardware continued to develop in 2020, with the launch of several AI chips customized for specialized tasks. While an ordinary processor is capable of supporting AI tasks, AI-specific processors are modified with particular systems that can optimize performance for tasks like deep learning. As AI applications become more widespread, any increase in performance or reduction in cost can unlock more value for companies that operate a wide network of data centers for commercial cloud services, and can facilitate the company’s internal operations.

Source: Baidu

Baidu’s innovations. At Baidu World 2020, the company offered a glimpse into its next-generation AI processor, the Kunlun 2, which it plans to put into mass production in early 2021. The chip uses 7 nanometer (nm) processing technology and its maximum computational capability is over three times that of the previous generation, the Kunlun 1. The Kunlun chips are characterized by high performance, low cost, and high flexibility, which can support a broad range of AI applications and scenarios, helping foster greater AI adoption and reducing usage costs. More than 20,000 Kunlun 1 chips have now been deployed to support Baidu’s search engine and Baidu Cloud partners since they launched in 2018, empowering industrial manufacturing, smart cities, smart transportation, and other fields.

This content was produced by Baidu. It was not written by MIT Technology Review’s editorial staff.

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Facebook predicts ‘significant’ obstacles to ad targeting and revenue in 2021



While Facebook’s fourth quarter earnings report included solid user and revenue numbers, the company sounded a note of caution for 2021.

In the “CFO outlook” section of the earnings release, Facebook said it anticipates facing “more significant advertising headwinds” this year.

“This includes the impact of platform changes, notably iOS 14, as well as the evolving regulatory landscape,” the company wrote. “While the timing of the iOS 14 changes remains uncertain, we would expect to see an impact beginning late in the first quarter.”

Facebook has already been waging a bit of a campaign against Apple’s upcoming privacy changes, which will require app developers to ask users for permission in order to use their IDFA identifiers for ad targeting — although the PR focus has been the impact on small businesses, not Facebook.

Facebook also highlighted two broad economic trends that it says has benefited from during the pandemic: The “ongoing shift towards online commerce” and “the shift in consumer demand towards products and away from services.” But again, it took a cautious stance, writing that “a moderation or reversal in one or both of these trends could serve as a headwind to our advertising revenue growth.”

As for those fourth quarter earnings earnings, Facebook reported $28.1 billion in revenue, of which $27.2 billion came from ads, with earnings per share of $3.88. Wall Street analysts had predicted EPS of $3.22 and revenue of $26.4 billon.

Facebook also reported an average of 1.84 billion daily active users and 2.80 billion monthly active users for the quarter, up 11% and 12% year-over-year, respectively.

“We had a strong end to the year as people and businesses continued to use our services during these challenging times,” said CEO Mark Zuckerberg in a statement. “I’m excited about our product roadmap for 2021 as we build new and meaningful ways to create economic opportunity, build community and help people just have fun.”

As of 4:45pm Eastern, Facebook shares were up 0.7% in after-hours trading.

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How trading apps are responding to the GameStop fustercluck



The furor surrounding GameStop and its stock price has consumed social media, business television, and the hopes and dreams of many retail investors. It has even convinced some folks that causing short-term economic damage to a few hedge funds is similar to shaking up the global financial market.

It isn’t, but a lot of folks are doing some downright risky things with their personal capital all the same. And some of them are making those investments — bets, let’s be honest — on platforms that have lowered barriers to buying and selling stocks by cutting trading fees to zero. Apps and services like Robinhood, Public, M1 Finance and Freetrade.

After noting reports that some traditional brokers were limiting access to GameStop and other so-called meme stocks, TechCrunch was curious what the newer, app-based investing services were doing for their own users.

A spokesperson for M1 Finance, a Midwest-based consumer fintech player that offers a basket of banking and investing services — more on its growth here and here — told TechCrunch via email that it wasn’t taking “specific” steps regarding individual stocks.

But the company also provided a statement from its CEO, Brian Barnes. In his comment, Barnes drew a delineation between investing, and trading, which he likened to a casino, adding that his firm “question[s] whether short-term trading is predictable, sustainable or repeatable.”

It isn’t for nearly anyone, of course. Barnes went on to say that his company thinks that “ownership of great companies and assets at reasonable prices that compound for long periods of time is the most straightforward and repeatable way to build wealth,” and that they have focused their company more around that ethos, “forego[ing] the mania of the moment.”

Turning to the well-known Robinhood, an impressive 2020 growth story, TechCrunch asked the same question regarding warnings or other guardrails for users concerning certain equities.

In an email a Robinhood spokesperson directed TechCrunch to a comment that its CEO, Vlad Tenev, made on CNBC earlier today:

Like other brokerages do, we monitor volatility and we take steps as appropriate like raising the margin requirements. I do think it’s wrong to assume though that most of our activity is characterized by trading of volatile stocks. As I’ve said before, most of our customers are what’s called buy and hold. They deposit and buy over the long term.

Robinhood changed margin requirements for GameStop and AMC Entertainment to 100%, TechCrunch understands. And like M1, Robinhood doesn’t allow users to short equities. So, there’s that.

Something notable about the companies we are discussing is that not one of them wants to be labeled as the place where folks like to trade a lot. Which amuses me as cutting fees to zero, which they have largely done, is at once a great way to democratize investing, and, also, a great way to encourage folks to trade more frequently. And as the apps and services that offer free trading often make money when users trade (read this), their chatter about their users being focused on buying and holding always rings slightly thin.

Anyhoo, some apps are going as far as adding warnings. Public, a company that TechCrunch recently covered, said that the company has added “‘High Risk’ safety labels” to the meme stocks that are causing so much ruckus.

Public has long had a stated focus on building community over trading, which led to us having a question or two about when it is going to kickstart its monetization plans. The company did just hire a CFO, which makes this move appear in concert with its general ethos, so more to come there we presume.

And, finally, U.K.-based Freetrade. TechCrunch has covered the service before, making it a good company to rope into this group. Per the company, Freetrade restricts small-cap stocks to the subscription tier of its service, which should limit access amongst its user base to GameStop and other memetic equities.

The company also stressed that it does not offer options or “any other form of leveraged derivatives” and has made “huge investment in investor education and financial literacy.”

So there’s a general bent toward either building products that are not tuned for day trading in silly stocks or providing some protection against users’ worst instincts amongst the cohort of companies that have also made it inexpensive to trade. There’s tension there, akin to this.

But they can only do so much. People are dumb, and it’s not looking like that’s going to get much better anytime soon.

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SoftBank teams with home goods maker Iris Ohyama for new robotics venture



You’d be forgiven for being underwhelmed by the output from SoftBank Robotics thus far. The firm’s best-known product to date is almost certainly Pepper, a humanoid robot designed for greeting and signage that grew out of it 2015 acquisition of French robotics company, Aldebaran.

There’s also the matter of the investment firm’s acquisition and eventual sale of Boston Dynamics. The deal certainly went a ways toward accelerating the company’s go-to-market approach, but Boston Dynamics changed hands fairly quickly, when it was sold to Hyundai late last year (SoftBank maintains 20%).

The latest wrinkle in SoftBank’s robotic ambitions is nothing if not interesting. The firm announced today that it is joining forces with Iris Ohyama. The Japanese brand, which will hold a 51% stake in the venture (with SoftBank controlling the remainder), is best known for its home goods. The company makes a broad range of products, that includes, as Reuters put it, “everything from rice to rice cookers.”

You’ll be able to add robotics to that list, soon enough. The newly formed Iris Robotics has set an extremely aggressive goal of $965 million in sales by 2025. In a joint press release, the company noted Covid-19-related concerns as a major catalyst in the launch of the division. Certainly that makes strategic sense. There’s little question that the past year has kickstarted serious interest in robotics and automation.

The first couple of products from the venture don’t appear especially ambitious out of the gate, however. To start, it seems they’ll be rolling out “Iris Editions” of a pair of existing devices: Bear Robotics’ restaurant robot Servi and cleaning robot, Whiz.

Here’s a quote from SoftBank Robotics CEO (forgive the Google translate),

With the urgent need to realize the new normal in the corona virus, various new expectations are being placed on robots. This strong partnership with Iris Ohyama is a huge step forward for the expansion and penetration of robot solutions. Taking full advantage of the strengths of both companies, we will respond quickly to the challenges facing society.

Certainly the technical ambitions seem more modest than what the folks at companies like Boston Dynamics are currently working on, but Iris Ohyama seems well positioned to make some headway in the home robotics category to start.


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