Once upon a time, the U.S. and China were buddies, exporting and importing from each other with ease. However, President Trump’s recent actions regarding trade with China is certainly putting a damper on things.

It seems that Chinese companies have moved past the need to import certain products, like smartphone chips, from the U.S. – something they previously relied heavily on by working with American companies like Qorvo, Inc. in North Carolina, Skyworks, Inc. in Massachusetts, Broadcom, Inc. in California, and Cirrus Logic in Texas.

Since the ban in May, Trump specifically barred shipments from the U.S. from companies like Qualcomm and Intel Corp to companies like Chinese tech conglomerate, Huawei Technologies Co. But much like the bans that came before the Trump administration, it didn’t last long. With tensions high, the U.S. actually recently started rolling back some aspects of the ban and started making exceptions that allow American tech companies to continue to work with Chinese companies like Huawei.

Of course, China’s lack of U.S. parts hasn’t stopped them from rolling out new and improved products. As a matter of fact, in September, Huawei unveiled its newest phone, the Mate 30, which boasts highly-desired features, such as a curved screen and a wide angle camera. This makes the phone a pretty solid competitor of Apple’s newest iPhone, the iPhone 11, of which China was sent 10 million of in September and October.

After Huawei’s announcement, investment and banking firm UBS, and Japanese technology lab Fomalhaut Techno Solutions, partnered up and took to their labs to analyze the phone’s components. Their analysis was simple and straightforward. They found that there were absolutely zero American components in the phone. In fact, the chips in the Mate 30 are actually from Huawei’s in-house chip design agency, HiSilicon. They also provided Huawei with WiFi and Bluetooth chips. With HiSilicon’s 20 + years experience in the industry, 200+ chipsets, and 8000+ patents, it’s no wonder U.S. chip companies are getting nervous. Qualcomm, for example, announced a 31-40% decrease in estimated chip shipments over the next year.

Although the chip ban has made a big impact on larger U.S. companies who make and supply chips to China, there are still many other businesses that have been affected in Trump’s trade war. As it happens, U.S. Commerce Secretary Wilbur Ross recently confessed that, since May, when the ban was put in place, the U.S. has received at least 260 requests, asking that they excuse them from the ban and be allowed to work with China as they previously had.

But really, at the end of the day, with so many American companies relying on China for both import and export, it’s probable that the ban will be short-lived and that exceptions won’t need to be made. As Americans, we can be hopeful that the end-result of this trade war will be a positive one, but only time will tell.

Musicians, listen up, there’s a new kid in town, its name is DeepComposer and it’s coming to take your creativity and turn it up to 11.

Artificial Intelligence has taken a leap into what has long been considered the “pinnacle of human creativity”, as Amazon revealed what is said to be the world’s first machine learning-enabled keyboard capable of creating music.

Amazon unveiled its AWS DeepComposer keyboard Monday during AWS re:Invent, a learning conference Amazon Web Services hosted for the global cloud computing community in Las Vegas.

Demonstrating DeepComposer’s abilities, Dr. Matt Wood, Amazon’s VP of Artificial Intelligence, played a snippet of Beethoven’s “Ode to Joy” and then let the keyboard riff on it with drums, synthesizer, guitar, and bass, sharing a more rockin’ version of the masterpiece.

Generative AI, is considered by scientists at MIT to be one of the most promising advances in AI in the past decade, Wood told the crowd. Generative AI allows for a machine not only to learn from example, as a human would but to take it next level and connect the dots, making the next creative step to composing something completely new.

“It [Generative AI] opens the door to an entire world of possibilities for human and computer creativity, with practical applications emerging across industries, from turning sketches into images for accelerated product development, to improving computer-aided design of complex objects, Amazon said on its AWS re:Invent website.

How does it work? The Generative AI technique pits two different neural networks against each other to produce new and original digital works based on sample inputs, according to Amazon. The generator creates, the discriminator provides feedback for tweaks and together they create “exquisite music”, Wood explained.

A user inputs a melody on the keyboard, then using the console they choose the genre, rock, classical, pop, jazz or create your own and voila, you have a new piece of music. Then, if so desired users can share their creations with the world through SoundCloud.

This is the third machine learning teaching device Amazon has made available, according to TechCrunch. It introduced the DeepLens camera in 2017 and in 2018 the DeepRacer racing cars. DeepComposer isn’t available just yet, but AWS account holders can sign up for a preview once it is.

Artificial intelligence (AI) is racist. Okay, fine, not all AI are racist (#NotAllAI), but they do have a tendency towards biases. Just look at Microsoft’s chatbot, Tay, which managed to start spewing hateful commentary in under 24 hours. Now, a chatbot isn’t necessarily a big deal, but for better or worse, AI is being used in increasingly crucial ways.

A biased AI could, for instance, change how you are policed, whether or not you get a job, or your medical treatment.

In an attempt to understand and regulate these systems, New York City created a task force called the Automated Decision Systems (ADS) Task Force. There’s just one problem: this group has been a total disaster.

When it was formed in May of 2018, the outlook was hopeful. ADS was comprised of city council members and industry professionals in order to inspect the city’s use of AI and hopefully come to meaningful calls for action. Unfortunately, the task force was plagued with troubles since the beginning.

For example, although ADS was created to examine the automated systems New York City is using, they weren’t granted access. Albert Cahn, one of the members of the task force, said that although the administration had all the data they needed, ADS was not given any information.

Sounds frustrating, right? One potential reason for this massive hiccup is the fact the administration was relying on third party systems which were sold by companies looking to make a profit. In this case, it makes sense that a company would like to avoid being scrutinized: it could easily lead to greater regulation or at the very least, a broader understanding of how their systems really worked.

Another overarching problem was the struggle to define artificial intelligence at all. Some automated systems do rely on complex machine learning, but others are far simpler. What counts as an automated system worth examining? The verdict is still out.

In the big scheme of things, AI tech is still in its infancy. We’re just starting to grasp what it’s currently capable of, much less what it could be capable of accomplishing. To add to the complications, technology is evolving at a break-neck speed. What we want to regulate now might be entirely obsolete in ten years.

Then again, it might not. Machines might be fast to change, but their human creators? Less so. Left unchecked, it’s debatable about whether or not creators will work to remove biases.

NYC’s task force might have failed – their concluding write-up was far from ideal – but the creation of this group signals a growing demand for a closer look at the technology making life-changing decisions. The question now? Who is best suited for this task.