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UK unveils law to fine social media firms which fail to remove online abuse

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By Michael Holden

LONDON (Reuters) – Britain said on Wednesday a planned new law would see social media companies fined up to 10% of turnover or 18 million pounds ($25 million) if they failed to stamp out online abuses such as racist hate crimes, while senior managers could also face criminal action.

The Online Safety Bill also seeks to strengthen the right to freedom of expression, and ensure democratic political debate and journalistic content is protected, the government said.

“It’s time for tech companies to be held to account and to protect the British people from harm. If they fail to do so, they will face penalties,” interior minister Priti Patel said.

Tech firms have been accused of doing far too little to address online abuse, with soccer clubs and other sporting authorities boycotting the world’s biggest social media platforms last month to highlight the growing problem.

The bill will place a duty of care on social media firms and websites to ensure they take swift action to remove illegal content, such as hate crimes, harassment and threats directed at individuals, including abuse which falls below the criminal threshold.

There will also be a requirement to remove and limit the spread of terrorist material, suicide content and child sexual abuse, which they would need to report to the authorities.

Those companies which fail to do so face hefty fines from regulator Ofcom which can also block access to their sites.

“The draft Bill contains reserved powers for Ofcom to pursue criminal action against named senior managers whose companies do not comply with Ofcom’s requests for information,” the government said. “These will be introduced if tech companies fail to live up to their new responsibilities.”

The proposed law will also require companies to safeguard freedom of expression, and reinstate material unfairly removed.

It will also forbid tech firms from discriminating against particular political viewpoints, and Ofcom will hold them to account for the arbitrary removal of journalistic content, the government added.

($1 = 0.7068 pounds)

(Reporting by Michael Holden)

Image Credit: Reuters

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Source: https://datafloq.com/read/uk-unveils-law-fine-social-media-firms-fail-remove-online-abuse/14589

Big Data

Facebook Launches One of the Toughest Reinforcement Learning Challenges in History

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Facebook Launches One of the Toughest Reinforcement Learning Challenges in History

The FAIR team just launched the NetHack Challenge as part of the upcoming NeurIPS 2021 competition. The objective is to test new RL ideas using a one of the toughest game environments in the world.




Image Credit: Facebook Research

 

I recently started a new newsletter focus on AI education and already has over 50,000 subscribers. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Please give it a try by subscribing below:

Image

Reinforcement learning(RL) has been at the center of some of the most impressive achievements in artificial intelligence(AI) in the last decade. From DeepMind’s famous AlphaGo to milestones in games such as StarCraft II, Dota 2 or Minecraft, RL remains one of the fastest growing areas in the deep learning space. Despite all its success, Facebook AI Research(FAIR) believes that RL needs to be pushed to new levels and, for that, they are turning their attention to a new game: NetHack.

The FAIR team just launched the NetHack Challenge as part of the upcoming NeurIPS 2021 competition. The objective is to test new RL ideas using a one of the toughest game environments in the world.

NetHack and RL

 
NetHack is a traditional dungeon game that has been under development since the 1980s and its incredibly tough to master for new players. For once, mistakes in NetHack have a disproportional cost. Once a player dies, the game starts from scratch in a completely different dungeon. To complete the game successfully, a player needs to execute about 25–50x more steps than in StarCraft. Additionally, the solution to many problems in NetHack require creativity and consulting external knowledge sources which results incredibly hard to model from a strategic standpoint.



Image Credit: Facebook Research



Image Credit: Facebook Research

 

From the RL perspective, NetHack presents a unique set of challenges:

  • Agents cannot reset the environment so optimization methods such as Monte Carlo Tree Search are useless in that type of setting.
  • Exploration is even more important given the partial completeness of the environment.
  • The high variability of changes in the environment requires rapidly adaptative RL techniques.

Among other things, the NetHack challenge should bring a new set of RL methods that can operate in highly complex environments in which errors have a significant cost. This should help advance research in areas such as navigation or many industrial environments that share some macro-characteristics with NetHack. Can’t wait to see the first wave of submissions.

 
Original. Reposted with permission.

Related:

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://www.kdnuggets.com/2021/06/facebook-launches-toughest-reinforcement-learning-challenges.html

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Big Data

Facebook Launches One of the Toughest Reinforcement Learning Challenges in History

Published

on

Facebook Launches One of the Toughest Reinforcement Learning Challenges in History

The FAIR team just launched the NetHack Challenge as part of the upcoming NeurIPS 2021 competition. The objective is to test new RL ideas using a one of the toughest game environments in the world.




Image Credit: Facebook Research

 

I recently started a new newsletter focus on AI education and already has over 50,000 subscribers. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Please give it a try by subscribing below:

Image

Reinforcement learning(RL) has been at the center of some of the most impressive achievements in artificial intelligence(AI) in the last decade. From DeepMind’s famous AlphaGo to milestones in games such as StarCraft II, Dota 2 or Minecraft, RL remains one of the fastest growing areas in the deep learning space. Despite all its success, Facebook AI Research(FAIR) believes that RL needs to be pushed to new levels and, for that, they are turning their attention to a new game: NetHack.

The FAIR team just launched the NetHack Challenge as part of the upcoming NeurIPS 2021 competition. The objective is to test new RL ideas using a one of the toughest game environments in the world.

NetHack and RL

 
NetHack is a traditional dungeon game that has been under development since the 1980s and its incredibly tough to master for new players. For once, mistakes in NetHack have a disproportional cost. Once a player dies, the game starts from scratch in a completely different dungeon. To complete the game successfully, a player needs to execute about 25–50x more steps than in StarCraft. Additionally, the solution to many problems in NetHack require creativity and consulting external knowledge sources which results incredibly hard to model from a strategic standpoint.



Image Credit: Facebook Research



Image Credit: Facebook Research

 

From the RL perspective, NetHack presents a unique set of challenges:

  • Agents cannot reset the environment so optimization methods such as Monte Carlo Tree Search are useless in that type of setting.
  • Exploration is even more important given the partial completeness of the environment.
  • The high variability of changes in the environment requires rapidly adaptative RL techniques.

Among other things, the NetHack challenge should bring a new set of RL methods that can operate in highly complex environments in which errors have a significant cost. This should help advance research in areas such as navigation or many industrial environments that share some macro-characteristics with NetHack. Can’t wait to see the first wave of submissions.

 
Original. Reposted with permission.

Related:

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://www.kdnuggets.com/2021/06/facebook-launches-toughest-reinforcement-learning-challenges.html

Continue Reading

Big Data

Web Scraping With Python: BeautifulSoup Library

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BeautifulSoup Library | Web Scraping With Python: BeautifulSoup Library





















Learn everything about Analytics


Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://www.analyticsvidhya.com/blog/2021/06/web-scraping-with-python-beautifulsoup-library/

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Big Data

Web Scraping With Python: BeautifulSoup Library

Published

on



BeautifulSoup Library | Web Scraping With Python: BeautifulSoup Library





















Learn everything about Analytics


Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://www.analyticsvidhya.com/blog/2021/06/web-scraping-with-python-beautifulsoup-library/

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