Hive - Machine Learning Engineer


Hive is a full-stack deep learning platform helping to bring companies into the AI era. We take complex visual challenges and build custom machine learning models to solve them. For AI to work, companies need large volumes of high quality training data. We generate this data through Hive Data, our proprietary data labeling platform with over 1,000,000 globally distributed workers, generating millions of high quality pieces of data per day. We then use this training data to build machine learning models for verticals such as Media, Autonomous Driving, Security, and Retail.

The New Business of AI (and How It's Different From Traditional Software)


At a technical level, artificial intelligence seems to be the future of software. AI is showing remarkable progress on a range of difficult computer science problems, and the job of software developers – who now work with data as much as source code – is changing fundamentally in the process. Many AI companies (and investors) are betting that this relationship will extend beyond just technology – that AI businesses will resemble traditional software companies as well. Based on our experience working with AI companies, we're not so sure. We are huge believers in the power of AI to transform business: We've put our money behind that thesis, and we will continue to invest heavily in both applied AI companies and AI infrastructure. However, we have noticed in many cases that AI companies simply don't have the same economic construction as software businesses. At times, they can even look more like traditional services companies. Anecdotally, we have seen a surprisingly consistent pattern in the financial data of AI companies, with gross margins often in the 50-60% range – well below the 60-80% benchmark for comparable SaaS businesses.

Elon Musk says AI development should be better regulated, even at Tesla


Tesla CEO Elon Musk wants to see all artificial intelligence better regulated, even at his own company, he tweeted Monday (via TechCrunch). He made the remark in response to a piece about OpenAI by MIT Technology Review, which claimed that the AI organization, co-founded by Musk, has shifted from its mission of developing and distributing AI safely and equitably into a secretive company obsessed with image and driven to constantly raise more money. Musk has a history of expressing serious concerns about the negative potential of AI. He tweeted in 2014 that it could be "more dangerous than nukes," and told an audience at an MIT Aeronautics and Astronautics symposium that year that AI was "our biggest existential threat," and humanity needs to be extremely careful: With artificial intelligence we are summoning the demon. In all those stories where there's the guy with the pentagram and the holy water, it's like yeah he's sure he can control the demon.

How AI in Ecommerce Enables True Personalization: Q&A With Elizabeth Gallagher of Lineate


"It's machine learning's job to find patterns based on the data you give it to help you focus on the data points most likely to lead to conversion." Elizabeth Gallagher, chief revenue officer at Lineate talks about how machine learning (ML) and artificial intelligence (AI) are changing the game for ecommerce brands. With the use of predictive analytics, marketers can create personalized marketing campaigns. In this edition of MarTalk Connect, Gallagher shares the key data points marketers should use to provide personalized recommendations. She stresses how data-driven automation and machine learning are strategic assets to enhance the customer journey.

IntoTheBlock – Empowering Blockchain Intelligence


ITB is an intelligence company that uses machine learning and statistical modeling to deliver actionable intelligence for crypto assets. Our machine learning algorithms combine hundreds of factors to extract unique insights about your crypto asset portfolio. ITB provides insights about crypto assets that everyone, not only sophisticated traders, can understand. ITB creates a holistic view of a crypto asset by analyzing hundreds of on-chain and off-chain factors. ITB regularly produces new insights and indicators that reveal new intelligence about crypto markets.

Free Japanese-language medical app offers advice about coronavirus

The Japan Times

A Japanese medical advice app provider is making a limited time offer of a free app that allows users to seek advice from doctors about the coronavirus. The free service, in Japanese only, is provided by Agree, a company based in Tsukuba, Ibaraki Prefecture. It also operates a medical advice app called Leber. Users are asked to send information such as whether they have traveled to any places where COVID-19 has been confirmed or whether they have developed a fever. With about 120 doctors registered for the service, users receive advice in about 30 minutes about the urgency of their condition, such as if they are suspected of having pneumonia and if they should seek advice from a public health center.

See the logos AI generates for Apple, Google, and Uber


That's at least based upon a new Logo-Maker tool just launched in beta by Israel-based freelance marketplace Fiverr. The tool claims to be able to "make a professional logo in just a few clicks," using artificial intelligence, so we put it to the test and used the tool to create some alternate logos for today's biggest brands, including Apple, Google, McDonald's, Uber, and even our own Fast Company logo, just for good measure. The designs are every bit as generic as you might expect. To craft a logo, the user chooses up to three industry keywords from a list to clue the AI into the industry your business is in. There was no "technology" industry option, so let's just say it was a bit difficult to properly describe Apple or Google.

Digital India rolling - Is the Indian workforce ready for transformation?


The bouquet of AI, pushed by machine learning, computer vision and the Internet of Things (IoT), is speedily evolving as a significant universal purpose technology. Besides technology companies, it is currently being pursued across sectors ranging from manufacturing, agriculture, healthcare, retail, financial services, banking, national defence, and security to public utilities. "We encourage our engineers in India to constantly push the boundaries of AI and machine learning capabilities, with applications from risk, marketing, customer service to autonomous infrastructure...," said Jayanthi Vaidyanathan – Senior Director Human Resources, PayPal India. "We have formulated several Leadership programs to build mid and senior leadership; programs that focus on soft skills of the individuals be it in influencing, brand building, communication, to name a few and also a structured job rotation program to continuously create opportunities for the top talent to diversify and equip themselves with newer skills," she said. The Ministry of Commerce and Industry constituted a task force in 2018 to study'How AI is reshaping jobs in India'.

Why use Python for AI and Machine Learning?


Python has been appreciated for its relentless ascent to distinction over recent years. Supported for applications going from web advancement to scripting and procedure mechanization, Python is rapidly turning into the top decision among engineers for AI, ML, and profound learning ventures. Computer-based intelligence or artificial intelligence has created a universe of chances for application engineers. Computer-based information permits Spotify to prescribe artisans and melodies to clients, or Netflix to comprehend what shows you'll need to see straight away. It is additionally utilized widely by organizations in client assistance to drive self-administration and improve work processes and worker efficiency.

Mozilla DeepSpeech Gets Smaller


The latest release, version v0.6, comes with support for TensorFlow Lite, the version of TensorFlow that's optimized for mobile and embedded devices. This has reduced the DeepSpeech package size from 98 MB to 3.7 MB, and cut the English model size from 188 MB to 47 MB. The developers achieved the cut using post-training quantization, a technique to compress model weights after training is done.