Papers published at the Neural Information Processing Systems Conference.

Some attacks may still slip "under the radar" though, which is why tools that leverage machine-learning, like User and Entity Behavior Analytics (UEBA), are an important support to your SIEM as they will detect more unusual threats as well as greatly increase the overall fidelity of your security alerts. SIEM and UEBA are further supported by threat hunting tools that enable your hunt teams to track down any other threats that may still be lurking in your system. All three approaches are important to your threat detection and response ecosystem. Micro Focus is a global software company with 40 years of experience in delivering and supporting enterprise software solutions that help customers innovate faster with lower risk. Our portfolio enables our 20,000 customers to build, operate, and secure the applications and IT systems that meet the challenges of change.

ODSC is the best community data science event on the planet. There are other events that cover special topics, or industries, etc., but ODSC is comprehensive and totally community-focused: it's the conference to engage, to build, to develop, and to learn from the whole data science community. ODSC East 2020 is one of the largest applied data science conferences in the world. Our speakers include some of the core contributors to many open source tools, libraries, and languages. Attend ODSC East 2020 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field.

PyMARL is WhiRL's framework for deep multi-agent reinforcement learning and includes implementations of the following algorithms: PyMARL is written in PyTorch and uses SMAC as its environment. This will download SC2 into the 3rdparty folder and copy the maps necessary to run over. The config files act as defaults for an algorithm or environment. They are all located in src/config. All results will be stored in the Results folder.

Keeping abreast of shopping trends online is straightforward enough -- whole categories of startups achieve this with predictive modeling. But what about when that shopping takes place in-store? Tracking the behaviors of mall, outlet, and department store shoppers is of critical importance to physical store brands, particularly considering that the percentage of brick-and-mortar sales increased by 2% from $2.99 trillion in 2016 to $3.04 trillion in 2017. To meet this need, Miron Mironiuk founded Cosmose AI, a Shanghai-based analytics software provider that anticipates how people shop offline. Brands like Subway, Samsung, Walmart, Airbnb, Tencent, Burberry, Omnicom, Mercedes-Benz, Anheuser-Busch InBev, LVMH, Kering, L'Oréal, Gucci, Cartier, P&G, Nestle, and Coca-Cola use its tool suite to granularly track offline visitors' purchasing habits and target them with online ads via WeChat, Weibo, Facebook, Google, and over 100 other internet platforms.

Organizations are starting to see artificial intelligence (AI) as an integral part of their corporate strategy. With mass volumes of data flowing through omni-channel environments, AI is now a reality rather than something of science fiction or something that only applies to the big tech companies. The International Data Corporation (IDC) have said that they expect global spending on AI to reach as much as $77 billion by 2022, a three-fold increase on the reported 2018 investments. A recent Gartner report showed that 49% of Chief Information Officers (CIOs) have already changed business models within their enterprise or are currently doing so to incorporate new technologies such as AI. Vice President of Gartner, Andy Rowsell-Jones, has said that we are moving to a new digital era of information technology.

Chorus.ai's Smart Call Disposition now automatically detects cold call results to improve connection rates, drive top of the funnel pipeline and provide opportunities for rep coaching. San Francisco: Chorus.ai, a Conversation Intelligence Platform for high-growth sales teams, today announced the launch of Cold Call Central during Dreamforce and OpsStars 2019. Cold Call Central uses artificial intelligence to provide Sales and Sales Development leaders insights into cold calls to drive "booked" meetings and top-of-funnel results. This new customizable view in Chorus surfaces actionable insights that enable prospecting teams to identify top-performing talk tracks, enrich 1:1's with recommended calls that need coaching, build a strategy around improving connection rates, and drive better alignment between Sales Development Reps and Account Executives. This first-of-its-kind custom view, tailored for SDR and self-prospecting sales teams, is powered by Chorus's proprietary Smart Call Disposition feature.

Artificial intelligence is causing microcontrollers to achieve higher levels of functionality. FREMONT, CA: Memory and computing capabilities are not crucial to run AI algorithms anymore. Today, the smallest of systems, with minimum processing and storage, can support AI and ML programs. Microcontrollers with artificial intelligence have become feasible today. Unlike full-scale computers, microcontrollers are simple and using a programmer, one can execute codes in it.

Verdict lists ten of the most popular tweets on artificial intelligence (AI) in November 2019, 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. Vala Afshar, Chief Digital Evangelist at Salesforce, shared a video of an interview of Bill Gates at a talk show hosted by David Letterman in 1995. Bill Gates tries to explain the internet to Letterman in the video.

OpenSeq2Seq main goal is to allow researchers to most effectively explore various sequence-to-sequence models. The efficiency is achieved by fully supporting distributed and mixed-precision training. OpenSeq2Seq is built using TensorFlow and provides all the necessary building blocks for training encoder-decoder models for neural machine translation, automatic speech recognition, speech synthesis, and language modeling. Speech-to-text workflow uses some parts of Mozilla DeepSpeech project. Beam search decoder with language model re-scoring implementation (in decoders) is based on Baidu DeepSpeech.