While machine learning models need a lot of data and computing power, to drive most progress from these models through AI, researchers use …

Artificial Intelligence in Medicine Market research is an intelligence report with meticulous efforts undertaken to study the right and valuable …

Seven years ago, my student and I at Penn State built a bot to write a Wikipedia article on Bengali Nobel laureate Rabindranath Tagore's play "Chitra." First, it culled information about "Chitra" from the internet. Then it looked at existing Wikipedia entries to learn the structure for a standard Wikipedia article. Finally, it summarised the information it had retrieved from the internet to write and publish the first version of the entry. However, our bot did not "know" anything about "Chitra" or Tagore. It did not generate fundamentally new ideas or sentences.

Therefore, to mitigate such problems, researchers have developed state-of-the-art (SOTA) models to autodetect fake news on social media using sophisticated data science and machine learning techniques. In this work, then, we ask "what if adversaries attempt to attack such detection models?" and investigate related issues by (i) proposing a novel attack scenario against fake news detectors, in which adversaries can post malicious comments toward news articles to mislead SOTA fake news detectors, and (ii) developing Malcom, an end-to-end adversarial comment generation framework to achieve such an attack. Through a comprehensive evaluation, we demonstrate that about 94% and 93.5% of the time on average Malcom can successfully mislead five of the latest neural detection models to always output targeted real and fake news labels. Furthermore, Malcom can also fool black box fake news detectors to always output real news labels 90% of the time on average. We also compare Real Comment: admitting im not going to read this (...) our attack model with four baselines across two real-world Malcom: hes a conservative from a few months ago datasets, not only on attack performance but also on generated Prediction Change: Real News Fake News quality, coherency, transferability, and robustness. We release the source code of Malcom at https://github.com/lethaiq/MALCOM

… play fairway analysis, machine learning, advanced geostatistics and other techniques into a comprehensive, holistic, integrated exploration toolkit.

AI and machine learning network Fetch.ai has unveiled an outcome of its developer engagement project, which aims to make it easier to develop …

At an online event today, Daniel Ek, the founder of Spotify, said he would invest 1 billion euros ($1.2 billion) of his personal fortune in deeptech "moonshot projects", spread across the next 10 years. Ek indicated that he was referring to machine learning, biotechnology, materials sciences and energy as the sectors he'd like to invest in. "I want to do my part; we all know that one of the greatest challenges is access to capital," Ek said, adding he wanted to achieve a "new European dream". "I get really frustrated when I see European entrepreneurs giving up on their amazing visions selling early on to non-European companies, or when some of the most promising tech talent in Europe leaves because they don't feel valued here," Ek said. "We need more super companies that raise the bar and can act as an inspiration."

It was reported that Venture Capital investments into AI related startups made a significant increase in 2018, jumping by 72% compared to 2017, with 466 startups funded from 533 in 2017. PWC moneytree report stated that that seed-stage deal activity in the US among AI-related companies rose to 28% in the fourth-quarter of 2018, compared to 24% in the three months prior, while expansion-stage deal activity jumped to 32%, from 23%. There will be an increasing international rivalry over the global leadership of AI. President Putin of Russia was quoted as saying that "the nation that leads in AI will be the ruler of the world". Billionaire Mark Cuban was reported in CNBC as stating that "the world's first trillionaire would be an AI entrepreneur".

As artificial intelligence becomes part of our everyday lives, it is increasingly necessary to lay down rules to regulate it. The Parliament wants a framework which allows people to reap the benefits of AI, while minimising the risks. Our team of independent correspondents, based across Europe and beyond, are at the centre of geopolitical dynamics. We are united by our commitment to free and unbiased journalism, and our devotion to the concept of true and unfettered democracy. We take our job very seriously!

Machine learning may seem magical at times, but it's not.