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Don't Be Overwhelmed by NLP

#artificialintelligence

With enormous amount go textual datasets available; giants like Google, Microsoft, Facebook etc have diverted their focus towards NLP. Let's these Tweets put things into perspective: This is barely the tip of the iceberg. So while you were trying to understand and implement a model, a bunch of new lighter and faster models were already available. I read them all to realize most of the research is re-iteration of similar concepts. Learn to use what's available, efficiently, before jumping on to what else can be used In practice, these models are a small part of a much bigger pipeline.


iiot bigdata_2020-09-25_03-17-11.xlsx

#artificialintelligence

The graph represents a network of 1,276 Twitter users whose tweets in the requested range contained "iiot bigdata", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 25 September 2020 at 10:21 UTC. The requested start date was Friday, 25 September 2020 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 1-day, 17-hour, 36-minute period from Wednesday, 23 September 2020 at 06:09 UTC to Thursday, 24 September 2020 at 23:45 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.


#FinServ_2020-09-20_16-30-01.xlsx

#artificialintelligence

The graph represents a network of 2,995 Twitter users whose tweets in the requested range contained "#FinServ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 20 September 2020 at 23:42 UTC. The requested start date was Sunday, 20 September 2020 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 7,500. The tweets in the network were tweeted over the 13-day, 21-hour, 20-minute period from Sunday, 06 September 2020 at 01:03 UTC to Saturday, 19 September 2020 at 22:24 UTC.


Twitter's AI Has Racist Bias

#artificialintelligence

On Saturday, a user tested out racial discrimination existing in Twitter's AI photo tools using two strips of photos. Twitter crops pictures attached to a tweet, only showing the entire picture after a user clicks on it, to allow the tweet to be concise. Taking two photos--one of Mitch McConnell, a white US senator, and the other of former US president Barack Obama, who is Black--attached on a strip of white, the user tried to see which photos the microblogging platform will display in the tweet. In all his attempts, the user found that the AI displayed McConnell's photo over Obama's, even after changing all secondary features that could affect the order.


#iiot_2020-09-22_14-06-41.xlsx

#artificialintelligence

The graph represents a network of 2,121 Twitter users whose tweets in the requested range contained "#iiot", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 22 September 2020 at 21:13 UTC. The requested start date was Tuesday, 22 September 2020 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 16-hour, 57-minute period from Saturday, 19 September 2020 at 07:03 UTC to Tuesday, 22 September 2020 at 00:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.


futureofwork _2020-09-21_11-35-07.xlsx

#artificialintelligence

The graph represents a network of 4,813 Twitter users whose tweets in the requested range contained "futureofwork ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 21 September 2020 at 18:47 UTC. The requested start date was Monday, 21 September 2020 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 7,500. The tweets in the network were tweeted over the 3-day, 16-hour, 29-minute period from Thursday, 17 September 2020 at 07:31 UTC to Monday, 21 September 2020 at 00:00 UTC.


Twitter round-up: Google's neural machine translation system most popular AI tweet in August 2020

#artificialintelligence

Verdict lists ten of the most popular tweets on artificial intelligence (AI) in August 2020 based on data from GlobalData's Influencer Platform. The top tweets were chosen from influencers as tracked by GlobalData's Influencer Platform, which is based on a scientific process that works on pre-defined parameters. Influencers are selected after a deep analysis of the influencer's relevance, network strength, engagement, and leading discussions on new and emerging trends. Ronald van Loon, principal analyst and CEO of Intelligent World, shared a video from the World Economic Forum on a neural machine translation technology developed by Google to provide natural translation between different languages using artificial intelligence and deep learning. The system was also used to translate two languages without using English as a bridge.


AI Weekly: Cutting-edge language models can produce convincing misinformation if we don't stop them

#artificialintelligence

It's been three months since OpenAI launched an API underpinned by cutting-edge language model GPT-3, and it continues to be the subject of fascination within the AI community and beyond. Portland State University computer science professor Melanie Mitchell found evidence that GPT-3 can make primitive analogies, and Columbia University's Raphaël Millière asked GPT-3 to compose a response to the philosophical essays written about it. But as the U.S. presidential election nears, there's growing concern among academics that tools like GPT-3 could be co-opted by malicious actors to foment discord by spreading misinformation, disinformation, and outright lies. In a paper published by the Middlebury Institute of International Studies' Center on Terrorism, Extremism, and Counterterrorism (CTEC), the coauthors find that GPT-3's strength in generating "informational," "influential" text could be leveraged to "radicalize individuals into violent far-right extremist ideologies and behaviors." Bots are increasingly being used around the world to sow the seeds of unrest, either through the spread of misinformation or the amplification of controversial points of view.


iot machinelearning_2020-09-16_05-23-21.xlsx

#artificialintelligence

The graph represents a network of 1,495 Twitter users whose tweets in the requested range contained "iot machinelearning", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 16 September 2020 at 12:31 UTC. The requested start date was Wednesday, 16 September 2020 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 4-day, 7-hour, 25-minute period from Friday, 11 September 2020 at 16:35 UTC to Wednesday, 16 September 2020 at 00:01 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.


The artificial intelligence trying to level Twitter's toxic playing field

#artificialintelligence

Tech start-up Areto Labs noticed online abuse was stopping women from going into politics – so it did something about it. "Imagine you have a job interview and every day, for a month, you have to walk down a dark alley, knowing the worst people in the world are in that alley and they will yell and scream at you," proposes Aucklander Jacqueline Comer, a creative technologist. "If you knew that, you wouldn't apply for the job. And, unfortunately, that's what women in politics have to put up with." Most people in the public eye cop some online criticism, but women get some of the most violent.