Even just five years back, Artificial Intelligence (AI) was still the stuff of science fiction, confined to research labs and tech giants' showcases. Processing power capacity, availability of representative data, development of more powerful algorithms, adaption of user interfaces, and, last but not least, a willingness to get the right policies in place. These single-chip processors were originally designed for video games but their capacity now to handle parallelization of multi-data processing means they're lending themselves to the use of complex AI algorithms and neural networks. This kind of complex machine learning though represents a big user challenge.
The funding round was led by US venture capital firm Rethink Impact. Swedish fintech firm iZettle says it will receive €30 million in debt funding from the European Investment Bank (EIB) in the coming three years. The EIB financing will support iZettle in four business areas: development of payments infrastructure; insights and actions through machine learning and artificial intelligence (AI); digitalisation of commerce processes; and scaling legislative and compliance systems. It has also reached a "landmark milestone" (one of those is enough I think) of providing £1.5 billion funding to UK businesses.
HHMI's researchers have identified a new memory and learning mechanism that they called "behavioral time scale synaptic plasticity" (BTSP). Discoveries in neuroscience could be applied to the construction of advanced artificial neural networks, with the possibility of learning, growing, and adapting. Billions of neurons, each connected to other neurons, form a neural machine made of billions of synaptic connections allowing us to form memories, to perceive reality, to predict, to decide, and to act. And an artificial neuronal network with this property and these capabilities could approach the true "unsupervised" AI with human-like intelligence that we mentioned earlier.
It is critical to our mission to enable machine learning researchers with the most powerful training scenarios, and for us to give back to the gaming community by enabling them to utilize the latest machine learning technologies. At Unity, we wanted to design a system that provide greater flexibility and ease-of-use to the growing groups interested in applying machine learning to developing intelligent agents. The ML-Agents SDK allows researchers and developers to transform games and simulations created using the Unity Editor into environments where intelligent agents can be trained using Deep Reinforcement Learning, Evolutionary Strategies, or other machine learning methods through a simple to use Python API. As mentioned above, we are excited to be releasing this open beta version of Unity Machine Learning Agents today, which can be downloaded from our GitHub page.
Swedish payment terminal company iZettle has won €30 million (£26.6 million) in funding from the European Investment Bank (EIB) to explore artificial intelligence (AI) and machine learning for small businesses. AI and machine learning knowledge and technology are often geared towards big companies, and small businesses don't usually have the funds to develop solutions tailored to their needs. To tackle this problem, Stockholm-based iZettle plans to invest in research and development over the next three years, specifically to benefit smaller businesses. In January, it announced having raised €60 million (£53.2 million) to fund further growth, and said in July it was signing up 1,000 new businesses per day.
Feng Zhang, a pioneer of the revolutionary CRISPR gene-editing technology, TAL effector proteins, and optogenics, is the recipient of the 2017 $500,000 Lemelson-MIT Prize, the largest cash prize for invention in the United States. Prior to harnessing CRISPR-Cas9, Zhang engineered microbial TAL effectors (TALEs) for use in mammalian cells, working with colleagues at Harvard University, authoring multiple publications on the subject and becoming a co-inventor on several patents on TALE-based technologies. Zhang was also a key member of the team at Stanford University that harnessed microbial opsins for developing optogenetics, which uses light signals and light-sensitive proteins to monitor and control activity in brain cells. Zhang's numerous scientific discoveries and inventions, as well as his commitment to mentorship and collaboration, earned him the Lemelson-MIT Prize, which honors outstanding mid-career inventors who improve the world through technological invention and demonstrate a commitment to mentorship in science, technology, engineering and mathematics (STEM).
SAE International has created the now-standard definitions for the six distinct levels of autonomy, from Level 1 representing only minor driver assistance (like today's cruise control) to Level 6 being the utopian dream of full automation: naps and movie-watching permitted. Many of the features of AI-assisted driving center around increased safety, like automatic braking, collision avoidance systems, pedestrian and cyclists alerts, cross-traffic alerts, and intelligent cruise control. A connected vehicle could also share performance data directly with the manufacturer (called "cognitive predictive maintenance"), allowing for diagnosis and even correction of performance issues without a stop at the dealer. Although it may not at first appear directly tied to automotive AI, the health and medical industry stands to experience some significant disruptions as well.
With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-4, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. Join Cloud Expo @ThingsExpo conference chair Roger Strukhoff (@IoT2040), October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, for three days of intense Enterprise Cloud and'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets. Accordingly, attendees at the upcoming 21st Cloud Expo @ThingsExpo October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track.
Often, the complexity and cost of training neural networks leads companies to outsource development to larger tech firms. Now that facial recognition systems are becoming more common, imagine if the software failed to identify that person. Fortunately, by working out exactly how to confuse AI, researchers are getting closer to finding solutions. Instead of discouraging businesses from taking an open approach to software development, badnets should motivate them to enter more transparent relationships.
To achieve that objective, the machine learning or artificial intelligence application needs clean and well-organized information in a robust ecosystem architecture. Kylo is an open source solution for data ingestion and data lake management employing NiFi templates to build an ingestion pipeline with cleansing, wrangling, and governance to transform data into meaningful structures needed for machine learning and analytics. Pat Alvarado is a Teradata Certified Master providing technical consultation on analytic ecosystem architecture, workload distribution, and multi-genre analytics across multiple platform and analytics technologies. After developing firmware for his micro controller hardware designs, Pat moved into software engineering developing data management applications with open source GNU software on distributed UNIX servers and disk-less workstations based on the Berkeley Software Distribution (BSD) as a departure from the proprietary AT&T UNIX and became known as FreeBSD.