Collaborating Authors


Trump pardons Anthony Levandowski, who stole trade secrets from Google


Donald Trump is on his way out of the White House, but that didn't stop him from pardoning 73 people and commuting the sentences of another 70 people on the last day of his presidency. One name on that list is Anthony Levandowski, who was sentenced to 18 months in prison for stealing trade secrets from the Google-owned, self-driving car company Waymo. Levandowski was a co-founder of Google's self-driving car division before leaving the tech giant in 2016 to start a self-driving truck company called Otto. That company was subsequently acquired by Uber, and Waymo filed a lawsuit alleging that their confidential information ended up in the hands of Uber. Levandowski was looking at a 10-year sentence, but he eventually pleaded guilty to trade secret theft, thus reducing his prison sentence.

Apple Electronics: Inside the Beatles' eccentric technology subsidiary

Daily Mail - Science & tech

Say the word Apple today and we think of Steve Jobs' multi-billion-dollar technology company that spawned the iPhone and the Mac computer. But a decade before the California-based firm was even founded, Apple Electronics, a subsidiary of the Beatles' record label Apple, was working on several pioneering inventions – some of which were precursors of commonly available products today. Apple Electronics was led by Alexis Mardas, a young electronics engineer and inventor originally from Athens in Greece, known to the Beatles as Magic Alex. He died on this day in 2017, aged 74, and was one of the most colourful and mysterious characters in the Beatles' story. Dressed in a white lab coat in his London workshop, Mardas created prototypes of inventions that were set to be marketed and sold. These included the'composing typewriter' – powered by an early example of sound recognition – and a phone with advanced memory capacity.

Man sues police over a facial recognition-related wrongful arrest


A New Jersey man is suing the town of Woodbridge and its police department after he was falsely arrested following an incorrect facial recognition match. Nijeer Parks spent 10 days in jail last year, including a week in "functional solitary confinement," following a shoplifting incident that January. After officers were called to a Hampton Inn in Woodbridge, the alleged shoplifter presented them with a Tennessee driver's license, which they determined was fake. When they attempted to arrest him after spotting what appeared to be a bag of marijuana in his pocket, the man fled in his rental car. One officer said he had to leap out of the way or he would have been hit.

Flawed Facial Recognition Leads To Arrest and Jail for New Jersey Man

NYT > Technology

Facial recognition technology is known to have flaws. In 2019, a national study of over 100 facial recognition algorithms found that they did not work as well on Black and Asian faces. Two other Black men -- Robert Williams and Michael Oliver, both of whom live in the Detroit, Mich., area -- were also arrested for crimes they did not commit based on bad facial recognition matches. Like Mr. Parks, Mr. Oliver filed a lawsuit against the city over the wrongful arrest. Nathan Freed Wessler, an attorney with the American Civil Liberties Union who believes that police should stop using face recognition technology, said the three cases demonstrate "how this technology disproportionately harms the Black community."

Sonos is fighting a war to stay relevant


For Sonos, 2020 began in dramatic fashion. While the tech world was focused on CES, the company made a splash by suing Google for allegedly infringing five of its wireless speaker patents. Sonos said this was just a small portion of Google's overall infractions, noting that both Amazon and Google likely violated about 100 patents each. Google counter-sued in June, and Sonos filed more charges in September. Sonos is well within its rights to defend its patent portfolio -- and the company has been working on wireless music-streaming tech for longer than just about anyone, so it's entirely possible its claims have merit.

Ross Intelligence files counterclaim against Thomson Reuters after announcing cease of operations


Ross Intelligence, an artificial intelligence startup for the legal industry, has filed a counterclaim against Thomson Reuters as part of an ongoing legal battle between the two companies. The counterclaim was filed just days after Ross Intelligence publicly announced it is shutting down operations. In a company blog post from December 11, Ross Intelligence's founders stated the startup's platform will no longer be operational as of January 31. "We have not abandoned our vision for access to justice through the use of technology. We will continue to fight the good fight."

A New Lawsuit Reveals an Existential Debate in Sports Video Games


Three Californians say that the video game publisher Electronic Arts is secretly manipulating them. On Nov. 9, they filed a class-action lawsuit accusing EA of surreptitiously using a patented A.I. technology known as dynamic difficulty adjustment in its FIFA, Madden, and NHL games--three of the biggest sports games on the planet. The lawsuit claims EA is using the technology to unfairly increase the difficulty of multiplayer mode online matches in order to encourage players to spend real-world money to boost their chances of winning. EA has denied ever implementing the technology and has called the lawsuit "baseless." For years, players have been stewing over ideas of fairness and balance in games, feeling taken for granted at best and taken advantage of at worst. The class-action complaint, Zajonc et al. v. Electronic Arts, doesn't contain any evidence for its claim, but that's fairly typical for this sort of class-action complaint.

Time-series Change Point Detection with Self-Supervised Contrastive Predictive Coding Artificial Intelligence

Change Point Detection techniques aim to capture changes in trends and sequences in time-series data to describe the underlying behaviour of the system. Detecting changes and anomalies in the web services, the trend of applications usage can provide valuable insight towards the system, however, many existing approaches are done in a supervised manner, requiring well-labelled data. As the amount of data produced and captured by sensors are growing rapidly, it is getting harder and even impossible to annotate the data. Therefore, coming up with a self-supervised solution is a necessity these days. In this work, we propose TSCP2 a novel self-supervised technique for temporal change point detection, based on representation learning with Temporal Convolutional Network (TCN). To the best of our knowledge, our proposed method is the first method which employs Contrastive Learning for prediction with the aim change point detection. Through extensive evaluations, we demonstrate that our method outperforms multiple state-of-the-art change point detection and anomaly detection baselines, including those adopting either unsupervised or semi-supervised approach. TSCP2 is shown to improve both non-Deep learning- and Deep learning-based methods by 0.28 and 0.12 in terms of average F1-score across three datasets.

Nuix and H5 Announce Strategic Partnership to Streamline Classification of Corporate Data


H5 announced that it has teamed up with Nuix to integrate its document classification solutions with the market-leading Nuix processing engine. This strategic partnership will allow corporations to gain greater control of their data, prioritize downstream review and reduce the risks associated with sending data outside of the organization. Starting with the identification of privileged content and personally identifiable information (PII), this partnership enables H5 to expand its ability to identify and classify such documents behind the corporate firewall. Protecting sensitive data is business critical for many corporations driven in part by the rise of new regulatory requirements, data breaches and continued complexity in eDiscovery. However, for many corporations finding and categorizing PII and privileged data in the context of eDiscovery is a headache filled with manual processes and workarounds.

Reveal and Epiq Announce Artificial Intelligence Enterprise Licensing Agreement


Industry leaders expand relationship providing access to Reveal's AI technology to Epiq clients globally Reveal, a groundbreaking eDiscovery technology company, and Epiq, a global leader in the legal services industry, today announced a global enterprise license agreement for the use of Reveal's artificial intelligence technology. The new enterprise license provides all Epiq clients with expanded access to Reveal's artificial intelligence platform with Reveal's recently announced acquisition of NexLP, a leader in the legal artificial intelligence space. Reveal's artificial intelligence platform turns disparate, unstructured data into meaningful insights that can be used to deliver operational efficiencies and strategic advantages for use with eDiscovery cases and Investigations. "Epiq is excited to partner with Reveal as it expands its analytics and artificial intelligence offering through the acquisition of NexLP, a long standing and highly strategic partner of Epiq," said Doug Mazlish, SVP, strategic alliances. "We are looking forward to continuing to provide our clients best in class legal technology solutions in partnership with Reveal. Reveal's investment in NexLP will further fuel their innovation in artificial intelligence in the legal industry and allow Epiq to continue to be an innovation leader in the market."