Chips to perform AI inference on edge devices such as smartphones is a red-hot market, even years into the field's emergence, attracting more and more startups and more and more venture funding, according to a prominent chip analyst firm covering the field. "There are more new startups continuing to come out, and continuing to try to differentiate," says Mike Demler, Senior Analyst with The Linley Group, which publishes the widely read Microprocessor Report, in an interview with ZDNet via phone. Linley Group produces two conferences each year in Silicon Valley hosting numerous startups, the Spring and Fall Processor Forum, with an emphasis in recent years on those AI startups. At the most recent event, held in October, both virtually and in-person, in Santa Clara, California, the conference was packed with startups such Flex Logix, Hailo Technologies, Roviero, BrainChip, Syntiant, Untether AI, Expedera, and Deep AI giving short talks about their chip designs. Demler and team regularly assemble a research report titled the Guide to Processors for Deep Learning, the latest version of which is expected out this month.

Google Assistant users in India using KaiOS feature phones will now have access to Google Lens, a year after the capability first expanded to India. Now, anyone who owns a feature phone or other device built on the KaiOS operating system will be able to use Google Assistant to identify any text in the image and read it out loud or translate it to another language. Google first debuted Lens three years ago in the U.S. and brought it to India in 2019. Lens combines machine vision to see any text in an image, then applies the voice AI to read the words out loud in the original language or any number of other tongues. It can even define the words in the food label, graffiti, or, as in the example image, a street sign.

Google is doubling down on KaiOS, the "light" operating system that makes low-cost feature phones feel a little smarter. Today, the company announced that the Google Assistant will be upgraded with Voice Typing "over the coming months," allowing KaiOS users to dictate text messages, web searches and basically anything else that uses a text box. KaiOS and the Assistant can also be set to different languages, according to Google. That means you could read the phone's menus, icons and settings in English and then talk, text and search through the Assistant in Spanish. KaiOS, if you need a refresher, is a spiritual successor to the ultimately-doomed Firefox OS.

Last month, the music streaming arm of telecom company Jio, Reliance Jio Music, and music and audio streaming service Saavn merged to jointly strengthen their foothold in the digital music market, which is expected to cross $460 million (Rs.3,100 crore) in revenue by 2020. The two music streaming companies will be integrated into a combined $1 billion entity that leverages the media streaming expertise of Saavn with the 4G internet connectivity of telecom company Jio. Soon after the announcement of this merger, Reliance Industries Limited (RIL), also agreed to pick up a 72.69% stake in the AI-based online education startup Embibe, with a proposal to invest $180 million over the next three years. This foray of India's petrochemical giant Reliance in the startup industry was the culmination of a plan put into motion in 2016, when RIL's owner, the richest Indian on Forbes Billionaires 2018 list, Mukesh Ambani, addressed its 42nd annual general meeting in Mumbai. During the address he stated that Reliance Industries was setting up a $743 million (Rs.5,000 crore) fund, called the Jio Digital India Startup Fund, to invest in digital businesses.

Every piece of IT hardware runs on software, make no mistake. For the new era of mobile handheld devices to become truly smart smartphones, they will need to exhibit new software processing powers over and above the ability to'simply' take photos, play games and surf the web. To be clear, the next era of smart smartphones will feature an increasing amount of machine learning and Artificial Intelligence (AI). This assertion (or is it almost a truism?) is at the heart of Chinese telecommunications giant's strategy. The firm has (literally) etched AI into the DNA of the'chipset' of its new line of Mate Series devices running on the new Kirin 970, a product described as the first AI processor for smartphones with a dedicated Neural Network Processing Unit (NPU) i.e. neural being'like a brain'.

Taking a look back at seven days of news and headlines across the world of Android, this week's Android Circuit includes Samsung's efforts to spoil MWC, new images leaked of the Galaxy S8, asking if the new Nokia handsets are worthy of the Nokia name, a hands-on review of the Nokia 5, the LG G6 design, Huawei's new camera technology, the return of the BlackBerry keyboard, and the designer of the Psion PDA returning with an Android dream machine. Android Circuit is here to remind you of a few of the many things that have happened around Android in the last week (and you can find the weekly Apple news digest here). Although it had previously declared that it would not be announced the Galaxy S8 at this week's Mobile World Congress in Barcelona, the South Korean company announced when it would be announcing its new flagship. It looks like a tactical move to remind consumers not to fall in love with the new devices from MWC until it can consider Samsung's latest: But today's news about the Galaxy S8 launch wasn't about reassuring the public. It was about taking away some of the momentum that the S8's rivals could gain from Mobile World Congress.

There are more mobile phones than humans on earth. That presents a unique opportunity for big data and, more importantly, the insights from the data to be applied to greater social good. At this week's PAPIs Connect--a predictive application programming interface (API) conference in Valencia, Spain--Nuria Oliver, the scientific director of Telefonica's R&D program, spoke about how to adapt this data via machine learning. Today, we touch on two of the situations she presented where big data and machine learning gave insight into how governments can better address crises, whether it's a natural disaster or a disease outbreak. In this piece we aren't talking about personalized data or even that which we're offering via our social media accounts.