The state is the output of the vehicle's perception network (i.e. This has been suggested as a way to simulate road users' behaviour. What do you think of this approach?

When people hear the word'Artificial Intelligence' (AI), the first thoughts and images that come to mind are those fed to us by Hollywood movies of the past few decades and recently by Netflix web series such as Black Mirror. This fictional representation paints a dire picture of AI destroying or enslaving humanity, but this vision of AI is too farfetched and distorts what is really happening in the field. At a recently concluded conference and exhibition on the subject conducted by the Confederation of Indian Industries (CII), AI was talked about as more of a tool and the terms used were Augmented Intelligence and Machine Learning rather than AI. CII has initiated three outcome-based AI task forces on skill development, education and agriculture. Many pilot projects by these task forces are currently being conducted at various sites.

A step-by-step tutorial on how to adapt and finetune BERT for a Kaggle Challenge classification task: The Kaggle Toxic Comment Classification Challenge. This post covers pretty much everything from data processing to model modifications with code examples for each part. Results are in the top-10% of this $35.000

Whether it's allegations of ethnic cleansing in Myanmar, anti-Muslim violence in Sri Lanka or the "gilets jaunes" protests in France, it is clear that social media platforms are helping spread divisive messages online at an alarming rate and potentially fueling offline violence. But the debate is about whether these platforms are an essential cause, without which these events could not have happened, or merely reflect real-world tensions. Read more: Debate: The'gilets jaunes' movement is not a Facebook revolution Algorithmic amplification is when some online content becomes popular at the expense of other viewpoints. This is a reality on many of the platforms we interact with today. The history of our clicks, likes, comments and shares are the data powering the algorithmic engine.

Almost everything you hear about artificial intelligence today is thanks to deep learning. This category of algorithms works by using statistics to find patterns in data, and it has proved immensely powerful in mimicking human skills such as our ability to see and hear. To a very narrow extent, it can even emulate our ability to reason. These capabilities power Google's search, Facebook's news feed, and Netflix's recommendation engine--and are transforming industries like health care and education. But though deep learning has singlehandedly thrust AI into the public eye, it represents just a small blip in the history of humanity's quest to replicate our own intelligence.

A security flaw in gay dating app Jack'd has left private intimate photos publicly exposed on the internet. Anyone with a web browser who knows where to look can access millions of private photos, even if they do not have a Jack'd account. Researcher Oliver Hough told BBC News he had reported the flaw to Jack'd a year ago but it has still not been fixed. The company has not responded to a request for comment. News site The Register first reported the flaw on 5 February, even though it had not been fixed, in order to warn the app's users.

Musiio, a Singapore-based startup that uses AI to help digital music companies with discovery and creation, has pulled in a $1 million seed round. The capital comes from Singapore's Wavemaker Partners, U.S. investor Exponential Creativity Ventures and undisclosed angels. The deal represents the first outside round for Musiio, which was founded at the Entrepreneur First program in Singapore where CEO Hazel Savage, a former streaming exec, met CEO Aron Pettersson. It also makes Musiio the first venture capital-backed music AI startup in Southeast Asia and one of the most notable EF graduates from its Asian cohorts. We first wrote about Musiio last April when it had raised SG$75,000 ($57,000) as part of its involvement in EF, the London-based accelerator that has big ambitions in Asia.

On the one hand there is a service provided to users free of charge,

Artificial intelligence as a topic has long been a mix of both fascination and fantasy, the realm of both computer science and Hollywood movies. As AI and related sub-disciplines such as machine learning become a reality in our everyday lives, that fascination grows. Now, though, we're increasingly focused on how AI will actually impact us, from its applications in enterprise IT to much broader effects on jobs and the global economy, healthcare, government, and more. A recent string of TED Talks speak to this shift from the speculative to the practical: How will humans and omnipresent AI actually coexist? What benefits will AI bring, now and later?

An article in The New York Times, "The rise of the robot reporter", discusses the new machine learning tools such as Forbes' Content Management System called Bertie, The Washington Post's Heliograf, Bloomberg's Cyborg, and others used by Reuters, the Associated Press and The Guardian for a range of tasks in their newsrooms, providing further insight into how robots are taking over a growing number of jobs. As the article points out, a number of media, notably those with a financial focus, now use algorithms to analyze data such as quarterly earnings reports and that can then be used to chart their progress over time, detect anomalies, as well as writing up stories. Machine learning can now be put to a growing number of uses in a newsroom. I have seen journalists use powerful analytical tools to analyze graphs, write and document their articles, adding information from different sources, as well as identifying information that may come from suspicious sources. It is hardly surprising that Bloomberg and Reuters now compete to provide real time financial information with the same hedge funds that were previously their clients but that now have access to the same means and resources.