Last year, I participated in a discussion of The Human Use of Human Beings, Norbert Weiner's groundbreaking book on cybernetics theory. Out of that grew what I now consider a manifesto against the growing singularity movement, which posits that artificial intelligence, or AI, will supersede and eventually displace us humans. The notion of singularity – which includes the idea that AI will supercede humans with its exponential growth, making everything we humans have done and will do insignificant – is a religion created mostly by people who have designed and successfully deployed computation to solve problems previously considered impossibly complex for machines. They have found a perfect partner in digital computation, a seemingly knowable, controllable, machine-based system of thinking and creating that is rapidly increasing in its ability to harness and process complexity and, in the process, bestowing wealth and power on those who have mastered it. In Silicon Valley, the combination of groupthink and the financial success of this cult of technology has created a feedback loop, lacking in self-regulation (although #techwontbuild, #metoo and #timesup are forcing some reflection).

In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches have achieved surpassing results in natural language processing. The success of these learning algorithms relies on their capacity to understand complex models and non-linear relationships within data. However, finding suitable structures, architectures, and techniques for text classification is a challenge for researchers. In this paper, a brief overview of text classification algorithms is discussed. This overview covers different text feature extractions, dimensionality reduction methods, existing algorithms and techniques, and evaluations methods. Finally, the limitations of each technique and their application in the real-world problem are discussed.

A teenager in New York is suing one of the biggest companies in the world for $1 billion. A New York college student filed a lawsuit against Apple for $1 billion, claiming the company's alleged use of facial recognition software in its stores falsely linked him to a series of Apple store thefts. Ousmane Bah, 18, claims that he received a summons from a court in Boston saying that he stole $1,200 worth of Apple products in 2018, according to papers filed on Monday in Manhattan federal court. The products included Apple Pencils, which retail for $99 each. On the day of one of the thefts in Boston, Bah was attending his senior prom in Manhattan, according to the court documents.

The government will set guidelines by the end of March next year for preventing technology leaks from universities that conduct research with foreign firms, sources close to the matter said Wednesday. The move comes as the United States and China grow cautious about advanced technologies such as artificial intelligence being converted for military use. While Japan already regulates the disclosure of sensitive technologies and products by the nation's state organizations and companies to overseas firms under a foreign exchange and foreign trade law, university laboratories have been managing infrequent arrangements on their own, leading some experts to voice concerns about the risk of information leaks. The envisioned guidelines would require universities and other research institutions to set regulations on joint projects involving foreign entities. They will be based on the comprehensive innovation strategy adopted by the Cabinet in 2018 aimed at promoting university research on AI, biotechnology and other leading technologies.

When Seven Dreamers Laboratories Inc. unveiled its prototype laundry-folding robot in 2015, it generated a buzz, with people saying they couldn't wait to buy one if it ever went to market. But the AI-based tidying device dubbed Laundroid is apparently coming to an end before its commercial debut, as the Tokyo-based developer filed for bankruptcy Tuesday with the Tokyo District Court, citing insufficient funds to continue operations. A spokesperson for Seven Dreamers, a contest-winning startup that had received over ¥10 billion in funding, said development of robot is over for now. According to Teikoku Databank Ltd., a credit research company, Seven Dreamers Laboratories had accumulated ¥2.2 billion in debt as it struggled to ship the robot and invested heavily in research and development. After postponing its initial sales goal in fiscal 2017, it had to push back its goal for fiscal 2018, too.

How to Do It is Slate's sex advice column. Send your questions for Stoya and Rich to howtodoit@slate.com. I have been sexually active since I was 17. I am now 29 years old. A majority of the sex I had between 17 and 21 was only when I was drunk, so I don't remember most of it, but I know I didn't climax.

Ousmane Bah, an 18-year-old college student from New York, filed a lawsuit against Apple on Monday for allegedly relying on facial recognition systems that misidentified him as a serial shoplifter. The suit claims that Apple and its contractor, Security Industry Specialists, caused Bah to suffer emotional distress as a result. Apple has subsequently denied that it uses facial recognition in its stores. According to the lawsuit, Bah received a summons arraignment last summer from a Boston municipal court for the theft of $1,200 worth of products from an Apple Store in the city. The police report indicated that a Security Industry Specialists loss prevention associate saw the theft on a security video and recognized Bah from a similar incident at an Apple Store in Connecticut.

Conditional simple temporal networks with uncertainty (CSTNUs) allow for the representation of temporal plans subject to both conditional constraints and uncertain durations. Dynamic controllability (DC) of CSTNUs ensures the existence of an execution strategy able to execute the network in real time (i.e., scheduling the time points under control) depending on how these two uncontrollable parts behave. However, CSTNUs do not deal with resources. In this paper, we define conditional simple temporal networks with uncertainty and resources (CSTNURs) by injecting resources and runtime resource constraints (RRCs) into the specification. Resources are mandatory for executing the time points and their availability is represented through temporal expressions, whereas RRCs restrict resource availability by further temporal constraints among resources. We provide a fully-automated encoding to translate any CSTNUR into an equivalent timed game automaton in polynomial time for a sound and complete DC-checking.

On the first day of November last year, some 20,000 Google employees at more than 40 offices across the world staged a walkout protesting how the company had dealt with serious accusations of sexual assault and harassment and what many employees described as a culture of impunity for executives. The event was planned by a core group of seven organizers who work at Google. On Monday, two of those women, Meredith Whittaker and Claire Stapleton, shared examples of retaliation they've face from the company since on a Google-internal mailing list. Wired first reported the two were facing blowback from Google for helping to organize the protest. Stapleton is a 12-year veteran at Google.

Much of the discussion of nation-state competition in artificial intelligence (AI) focuses on relatively easily quantifiable phenomena including funding, technological advances, access to data and computational power, and the speed of AI industrialization. However, a central element of AI leadership is something much less tangible: control over the norms and values that shape the development and use of AI around the world. The U.S. government has overlooked this dimension of AI development for years, but the last couple months indicate the beginnings of a change of course. If the U.S. hopes to maintain global AI leadership, the government must continue to stake out a comprehensive positive vision, or we may find that the future of AI is a world few of us want to live in. Until recent months, the U.S. government had remained relatively quiet on the topics of AI values and ethics.