Distributed Training on Amazon SageMaker delivers new capabilities that can train large models up to two times faster than would otherwise be possible with today's machine learning processors Inc. company, announced nine new capabilities for its industry-leading machine learning service, Amazon SageMaker, making it even easier for developers to automate and scale all steps of the end-to-end machine learning workflow. Today's announcements bring together powerful new capabilities like faster data preparation, a purpose-built repository for prepared data, workflow automation, greater transparency into training data to mitigate bias and explain predictions, distributed training capabilities to train large models up to two times faster, and model monitoring on edge devices. Machine learning is becoming more mainstream, but it is still evolving at a rapid clip. With all the attention machine learning has received, it seems like it should be simple to create machine learning models, but it isn't. In order to create a model, developers need to start with the highly manual process of preparing the data.

This article is fourth in a 5-part series on predictions in AI in 2021 -- catch up on the first, second, and third in the series. Perhaps the most succinct summary of the relationship between artificial intelligence (AI) and data can be described as follows: an AI model is only as good as the data it was trained on. Training data serves as the foundation of AI solutions everywhere and can make or break their success. Data management is a key focal point for companies building machine learning (ML) models, and this domain will only continue to grow in importance in 2021 and beyond. In the coming years, it will be more evident than ever how steep the price is of getting this area of AI wrong.

Transparency, explainability, and trust are big and pressing topics in AI/ML today. Nobody wants to find themselves at the receiving end of a black box system that makes consequential decisions (e.g., about jobs, healthcare, citizenship, etc.), especially if those decisions are unfair, biased, or just plainly not in our favor. And most organizations agree that consumer trust and confidence that AI is being used ethically and transparently are keys to unlocking its true potential. And while there are literally hundreds of documents describing and prescribing AI principles, frameworks, and other good things, there haven't been any practical tools that could help with implementing transparency. On September 28, 2020, the Cities of Helsinki and Amsterdam jointly announced the launch of their public AI registers.

National Australia Bank (NAB) has signed an agreement with artificial intelligence (AI) specialist Rich Data Corporation to use its AI prediction and decisioning capability software Delta. Under the agreement, NAB would use Delta's credit risk management capability, which links traditional and alternative data sources to provide prediction and credit decisions, for its SME customers with little or no credit history or who might fall outside traditional credit bureau criteria. The capability will also use analytics and monitoring tools to identify portfolio risks and opportunities to support businesses that experience major change from events like the coronavirus pandemic. Commenting on the partnership with Rich Data Corporation, NAB executive innovation and partnerships Howard Silby said: Their Delta platform will enable us to innovate and accelerate our lending options, leveraging alternative data and AI techniques and providing a means to assess SMEs who fall outside traditional credit models. "We remain committed to finding new ways to serve and meet the needs of our small-business customers, as we pioneered with our NAB QuickBiz offering in 2016 and several innovations since."

Aggressive marketing language can often drive a lack of clarity around technical concepts. Somewhat surprising, is that confusion between RPA and AI is high even among organizations that have automation in place and have likely gone through the diligence and/or request for proposal (RFP) process to select their automation solution. More than 50 percent of CFOs and revenue cycle leaders in organizations that are actively using automation say they consider RPA to be a form of artificial intelligence. "RPA based bots can be good tools for automating simple, discrete, and static tasks," said Varun Ganapathi, co-founder and Chief Technology Officer at Alpha Health. "AI and machine learning based technologies are capable of automating much more complex tasks that require some degree of judgment or subject matter expertise. Additionally, AI and machine learning based solutions can have the ability to navigate changes or new variables without the need to reprogram or recode a bot every time something changes."

At a time when artificial intelligence algorithms are increasingly prevalent in our everyday lives (recruitment, customer relations, recommending content, banking and insurance, etc.), it is vital for Orange to ensure that the entire data value chain is managed responsibly and that potential discriminatory biases are identified and eliminated. The audit, carried out by Bureau Veritas, assessed Orange for its actions aimed at designing, developing and using inclusive artificial intelligence to promote diversity and avoid risks of discrimination before awarding the certification. The GEEIS-AI repository offers a way to raise awareness among the entire AI production chain, from design to operating the end product. In this way, a wide range of job lines and skills are at the service of the entire Orange ecosystem. This applies, in particular, to human resource management processes to guarantee they are not biased while encouraging diversity in AI job lines.

Bangkok Bank PLC announced the launch of its Thai language Artificial Intelligence (AI) powered chatbot that was built in-house in a joint collaboration with Singapore-based fintech startup Pand.ai. The chatbot called TT01 was a result of Bangkok Bank's innovation programme, InnoHub. The development began earlier this year and the chatbot was fully completed in October. The solution will be available to clients of Pand.ai. Meanwhile, Bangkok Bank will use this as a digital sales assistant on LINE for their sales and relationship managers, scheduled to launch in Q1 2021.

* EIB signs €20 million (DKK 149 million) loan agreement with Danish research and development company Evaxion Biotech A/S. * Evaxion will use financing for research and development into its proprietary artificial intelligence platforms used to identify novel vaccine and immunotherapy targets. * Transaction supported by European Commission through InnovFin – EU finance for innovators program, under the Infectious Diseases Finance Facility window. LUXEMBOURG and COPENHAGEN, Denmark, Dec. 09, 2020 (GLOBE NEWSWIRE) -- The European Investment Bank (EIB) has signed a €20 million loan agreement with Evaxion, supported by the Infectious Diseases Finance Facility window under the EU’s InnovFin – EU finance for innovators program, backed by the EU’s research and innovation program Horizon 2020, which guarantees EIB loans for highly innovative projects. The financing will support Evaxion’s research and development (R&D) investments in the use of artificial intelligence (AI) to determine the most suitable targets for immunotherapies for cancer and infectious diseases.The main focus of the research, Evaxion’s proprietary AI-based platforms, could potentially transform the drug discovery process for vaccines and immunotherapies. In particular, the infectious disease programs targeting Staphylococcus aureus and Pseudomonas aeruginosa aim to identify novel vaccines to address the resistance to common treatments developed by these pathogens. The EU financing will support the investments in Evaxion’s AI platforms, as well as its pre-clinical and clinical activity.Lars Wegner, CEO of Evaxion, said: “This loan agreement with the EIB underpins Evaxion’s position as a leader in the utilization of AI for discovery and development of novel vaccines and immunotherapies, and supports important research and development within our key programs. We are proud to be entering into this agreement with EIB, which is an example of critical financing being used to address some of the biggest challenges to human health.”EIB Vice-President Christian Kettel Thomsen stated: “As the EU bank, the EIB strives to ensure that high impact projects receive the financing they need. The EIB is delighted to be supporting Evaxion. The use of AI in the development of vaccines and immunotherapies is true innovation and is perfectly in sync with the EIB’s overarching priority: improving people’s lives. In recent years, the Bank’s investments in Denmark have been able to support many innovative companies, of which this is an excellent example.” Mariya Gabriel, European Commissioner for Innovation, Research, Culture, Education and Youth, added: “Protecting the health of our citizens and leading the digital transformation are key priorities underpinning Europe’s prosperity and growth. This EU-backed loan for Evaxion’s research using AI may help to transform the drug discovery process to treat cancer and infectious diseases.”The project not only strengthens European R&D, but is also contemplated to have an impact on the safeguarding and creation of highly skilled jobs in the EU. The research will be wholly carried out in Denmark, and is expected to contribute to technological advancements in artificial intelligence and its applications in healthcare. As such, the project is expected to bring important social benefits in terms of advances in research and alleviating the burden placed on healthcare services by the increased incidence of multi-resistant pathogens.Background Information:The European Investment Bank (EIB) is the long-term lending institution of the European Union owned by its Member States. It makes long-term finance available for sound investment in order to contribute towards EU policy goals. In 2019, the Bank provided over €850 million in loans for Danish projects in various sectors, including services, innovative industry and small and medium-sized enterprises.Under Horizon 2020, the EU research and innovation framework program for 2014-2020, the Infectious Diseases Finance Facility (IDFF) provides financial products ranging from standard debt to equity-type financing for amounts typically between €7.5 million and €75 million to innovative players active in developing innovative vaccines, drugs, medical and diagnostic devices or novel research infrastructure for combating infectious diseases. Project costs may include clinical trial costs, set-up of commercialization such as market access, development of prototypes or industrial roll-out of novel equipment, pre-clinical R&D costs and working capital requirement. This facility is delivered directly by the EIB, which has so far provided €241 million under the InnovFin IDFF.About Evaxion Evaxion Biotech A/S is an AI-immunology™ platform company decoding the human immune system to discover and develop novel, targeted immunotherapies to treat cancer and infectious diseases. Based on its proprietary and scalable AI-immunology core technology, Evaxion Biotech is developing a broad pipeline of novel assets which comprises three patient-specific cancer immunotherapies, two of which are in Phase 1/2 clinical development. In addition, the Company is advancing a portfolio of vaccines to prevent bacterial and viral infections with one program currently in preclinical development against S. aureus and skin and soft tissue infections (SSTI).Press contacts: European Investment Bank: Tim Smit, +352 691 286423, t.smit@eib.org European Commission: Flora Matthaes, +32 460 755148, flora.matthaes@ec.europa.eu Evaxion: Glenn S. Vraniak +1 (513) 476-2669, gvr@evaxion-biotech.com

Neptune Lines PCTCs feature METIS Ship Connect – the automated data acquisition solution whose accuracy is approved by Lloyds Register. The METIS platform uses a network of Wireless Intelligent Collectors to harvest machinery, navigation and operational data regardless of equipment supplier. Its ship performance analysis also integrates AIS data, data fetched from vessels' daily / arrival / departure regular reporting and weather forecasts to provide services such as automated noon reporting, analysis of technical and operational domains and weather-related reporting. Outputs include live dashboards showing the condition of main engines, diesel generators, ballast water treatment systems and other machinery as well as power and fuel consumption. However, the METIS platform also allows Neptune Lines management to visualize KPIs such as power vs speed under the full ship speed range and in all weathers using machine learning models and run'what if' routing scenarios to weigh up consequences for fuel and arrival times.

Nearly three years after it was first launched, Amazon Web Services' SageMaker platform has gotten a significant upgrade in the form of new features making it easier for developers to automate and scale each step of the process to build new automation and machine learning capabilities, the company said. As machine learning moves into the mainstream, business units across organizations will find applications for automation, and AWS is trying to make the development of those bespoke applications easier for its customers. "One of the best parts of having such a widely-adopted service like SageMaker is that we get lots of customer suggestions which fuel our next set of deliverables," said AWS vice president of machine learning, Swami Sivasubramanian. "Today, we are announcing a set of tools for Amazon SageMaker that makes it much easier for developers to build end-to-end machine learning pipelines to prepare, build, train, explain, inspect, monitor, debug and run custom machine learning models with greater visibility, explainability, and automation at scale." Already companies like 3M, ADP, AstraZeneca, Avis, Bayer, Capital One, Cerner, Domino's Pizza, Fidelity Investments, Lenovo, Lyft, T-Mobile, and Thomson Reuters are using SageMaker tools in their own operations, according to AWS.