US government agencies were ordered to scour their networks for malware and disconnect potentially compromised servers after authorities learned that the Treasury and Commerce departments were hacked in a monthslong global cyberespionage campaign discovered when a prominent cybersecurity firm learned it had been breached.

In a rare emergency directive issued late Sunday, the Department of Homeland Security's cybersecurity arm warned of an "unacceptable risk" to the executive branch from a feared large-scale penetration of U.S. government agencies that could date back to mid-year or earlier.

News of the hacks, first reported by Reuters, came less than a week after FireEye disclosed that nation-state hackers had broken into its network and stolen the company’s own hacking tools.

Stay Safe From Cybercrime

When a top cybersecurity firm gets hacked, it's time for the average netizen to take cybersecurity very, very seriously. 

COVID-19 has pushed all of our lives into becoming increasingly digital. However, with an increased digital presence and large stores of personal and professional data, the risk of becoming a victim to cybercrime increases.

Everybody knows about antiviruses and VPNs, but we wanted to dive deeper in the world of cybersecurity to find new and safe ways of keeping everything private and inaccessible to a stray hacker.

We’ve put together this list of Cybersecurity resources so that you can integrate cybersecurity measures seamlessly into your daily life. This list is more than just tools — it also has tips from important articles to help you better understand cybersecurity and its importance in today’s world.

DeepMind Hacks Protein Biology

Proteins are essential to life, supporting practically all its functions. They are large complex molecules, made up of chains of amino acids, and what a protein does largely depends on its unique 3D structure. Figuring out what shapes proteins fold into is known as the “protein folding problem,” and has stood as a “grand challenge” in biology for the past 50 years. 

According to DeepMind, this breakthrough demonstrates the impact AI can have on scientific discovery and its potential to dramatically accelerate progress in some of the most fundamental fields that explain and shape our world.

US vs Facebook

The US FTC and a group of US states filed two separate antitrust cases against Facebook, claiming the acquisitions of Instagram (2010) and WhatsApp (2014) were anti-competitive and led to privacy infringements, and that Facebook uses access to user data APIs selectively to squeeze out competing networks. Both cases call for Instagram and WhatsApp to be split apart, for controls on future mergers and acquisitions, and for vaguely-specified controls on future conduct by Facebook.

Untangling Instagram and WhatsApp from Facebook could be complicated and take years.

Facebook's antitrust woes extend beyond the US. Israel could reportedly impose a fine of hundreds of millions of shekels on Facebook for failing to adequately report a series of acquisitions it has made in the country.

Internet Companies Under EU Microscope

Companies like Facebook and Amazon could face fines of up to billions of euros if they flout new rules aimed at curbing online hate speech and the sale of illegal goods, according to a draft of the European Commission's upcoming Digital Services Act.

Under the proposals, which will be unveiled this week, Brussels will mandate that large online platforms - those that reach at least 45 million people across the 27-country bloc - must limit the ability of illegal material from spreading on their networks, provide regulators and outside groups with greater access to their internal data and appoint independent auditors that will determine if firms are compliant with the new rules.

Tech is becoming a regulated industry. These measures aim to control how all internet companies have to behave, as opposed to a single internet company like Facebook.

Binge Watching? Blame The Netflix AI!

If Netflix’s decisions on marketing its shows seem highly calculated... that’s probably because they were. Netflix has outlined how it uses AI to market shows and predict their success in ways that conventional box office numbers and Nielsen ratings likely couldn’t match. Effectively, it comes down to finding connections and determining the likely audience sizes.

The method relies on transfer learning, where the the parameters learned from a “source task” improve the performance of a “target task.” In this case, the source tasks are simple: what titles are comparable to a Netflix original, and what kind of viewership can the service expect?