Reddit has acquired short-form video platform and TikTok rival Dubsmash for an undisclosed sum, the companies announced. Dubsmash will keep its current platform and brand, while Reddit will integrate Dubsmash's video creation tools. "Dubsmash provides a welcoming platform for creators and users who are under-represented in social media," Reddit said. The site boasted over a billion video views per month in January 2020, according to TechCrunch. Back in 2015, though, Dubsmash was best known as a lip-syncing app you could use to create, but not post, videos.

These rules need to ensure that human dignity and human rights are respected and that AI systems are subject to meaningful human control, allowing humans to correct or disable them in case of unforeseen behaviour. Humans should therefore be identifiable and ultimately held responsible. MEPs agreed that lethal autonomous weapon systems (LAWS) should only be used as a last resort and be deemed lawful only if subject to human control, since it must be humans that decide between life and death. The text calls on the EU to take a leading role in promoting a global framework on the military use of AI, alongside the UN and the international community. The increased use of AI systems in public services, especially healthcare and justice, should not replace human contact or lead to discrimination, MEPs assert.

BEGIN ARTICLE PREVIEW: Hyundai is officially purchasing a controlling stake in robot maker Boston Dynamics from SoftBank in a deal that values the company at $1.1 billion, the company announced today. The deal has been in the works for a while, according to recent a report from Bloomberg, and marks a major step into consumer robotics for Hyundai. Hyundai is taking approximately an 80 percent stake in the company while its previous owner, Softbank, will retain around 20 percent through an affiliate. Hyundai says its investment will help its development of service and logistics robots, but that over time it hopes to build more humanoid robots for jobs like “caregiving for patients at hospitals.” Other areas of interest include autonomous driving and smart factories. Boston Dynamics started as a spin-off from the Massachusetts Institute of Technology. The company has created robots using DARPA funding, like BigDog, but is best known for the viral fame its robots ha

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.