For this edition focused on TV content, we're very happy to be hosted at ProSiebenSat.1. They will sponsor the venue, the food and the drinks! As there will be a security check at the entrance I'd like to kindly ask everyone to register on this Eventbrite page so I have a master list of names. IF YOUR NAME IS NOT ON THE LIST YOU WON'T GET IN. So make sure to register, pretty please.

Our platform is simple when it should be, and robust when you want it to be. We make it easy for you to easily tap into any part of our flow, with webhooks and a number of read and write APIs.

Salesforce will introduce artificial intelligence (AI) and predictive capabilities into its customer relationship management (CRM) product as soon as October as it starts to roll our Einstein across its cloud products. During a phone question and answer session last week general manager of Einstein, John Ball, said: "You will see [Einstein] powering AI across all of our clouds and there are many features coming. We do three releases a year and Einstein will be powering every release from now on, starting with the winter release in October." Salesforce is being coy in terms of pricing, saying that some capabilities will come with existing cloud licenses and editions, and some coming at a premium. The pricing of each feature will only be known once it is made generally available, except Community Cloud, Commerce Cloud and Analytics Cloud capabilities, which are included in existing licenses and detailed below.

This approach tends to teach to machines what humans like to listen to, without understanding what is recommended. It is a deaf approach that's trying to mimic the record dealer's behavior. It's not a DJ that builds a listening experience. It doesn't capture what the soundtrack of your life is. Collaborative filtering also tends to make predictable and familiar recommendations. This favors the rise of a popular artist dictatorship, harmful for the beautiful versatility of music.

For decades, futurists and science fiction writers predicted that smart machines would someday rival the intelligence of humans. Now, their forecasts seem to be coming true. Artificial intelligence, or AI, already exceeds human capability in certain fields. Machines can send and receive signals and analyze vast quantities of data faster than humans. They have learned to drive cars, manage stock portfolios and, through personal assistants such as Siri and Alexa, talk to us.

The company has also gone on to announce the formation of Salesforce Research, a unit which will do the research in deep learning, natural language processing along with computer vision, which can be used, so as to improve Salesforce products. The unit which is led by Salesforce chief scientist Richard Socher, formerly Co-Founder and Chief Executive of AI startup MetaMind, which Salesforce acquired earlier this year. In a press briefing in San Francisco, earlier this week, Socher goes on to decline to make up a statement on how many people were part of the team, although he did go on to state that some of Salesforce's 175 data scientists have gone on to join the newly organized division.

Customer relationship management and cloud computing giant Salesforce on Sunday announced the launch of "Einstein" -- an initiative that seeks to use artificial intelligence tools to automate tasks, predict customer behavior and enhance sales. With the move, Salesforce joins the likes of Google, Microsoft, IBM and Amazon in integrating AI and machine learning tools in its operations. "The strongest aspect of Einstein is that it is deeply embedded in the platform, it's just working automatically," Salesforce CEO Marc Benioff told USA Today. Einstein will use machine learning -- an integral part of most current AI-based technologies -- to sift through huge chunks of data stored on Salesforce's servers. This, the company states, can help in predicting which customers are likely to buy products and what those products are, thereby helping salespeople prepare better marketing pitches. In addition, Einstein will also use predictive analytics to compile a list of sales leads that are likely to be successful.

According to VentureBeat, the cyberattack knocked off Battle.net servers and kept players offline for some time. The site also reported that players took to social media to share that they were experiencing difficulties in accessing the games they were playing. Blizzard took to Twitter to confirm that a DDoS attack was preventing their network providers from functioning well. The publisher wrote: "We are currently monitoring a DDOS attack against network providers which is affecting latency/connections to our games." VentureBeat also pointed out that the Sept. 18 incident was the third time that Blizzard's servers went down in a week. However, the first two incidents -- reportedly took place on Sept. 13 and Sept. 16 -- were problems with authentication servers, while the latest one was an assault on the company's networks.

Technology is getting smarter, faster. Experts including the authors of The Second Machine Age, Erik Brynjolfsson and Andrew McAfee, examine the impact that "thinking" machines may have on top-management roles. The exact moment when computers got better than people at human tasks arrived in 2011, according to data scientist Jeremy Howard, at an otherwise inconsequential machine-learning competition in Germany. Contest participants were asked to design an algorithm that could recognize street signs, many of which were a bit blurry or dark. Humans correctly identified them 98.5 percent of the time. At 99.4 percent, the winning algorithm did even better. Or maybe the moment came earlier that year, when IBM's Watson computer defeated the two leading human Jeopardy!

Three-week old social network Gab.ai gains traction among alt-right users; has LAUNCH Ticker