They do not want to watch their mother botch sandwich making because of their bad directions.
My five- and seven-year-old constantly fight over who gets the iPad first. We have one, and they get to use it in tiny doses, usually when I’m at my wit’s end. Their favorite app? ScratchJr, MIT’s go-to coding tool for kids. They like to code. No. They love to code, like the good little 21st-century humanoids they are.
They love coding so much and I am so unwilling to give them their own devices that I decided to try something new. It’s also something that sounds so counterintuitive it actually might work: screen-free coding.
With the latest studies presenting a pretty damning picture of screen time’s effects on children’s development, I’m delighted to hear that screen-free coding is all the rage now. It is exactly what it sounds like: a way to explore the key concepts of coding sans screen. At its core, coding is simply giving a set of specific directions to someone or something to produce a desired result. Nothing in that definition demands a screen.
It is about computational thinking though and the ability to identify and solve problems by breaking the problem and solution into workable chunks. You could teach your kid computational-thinking strategies by asking them to tell you how to make a peanut butter sandwich and it meets the screen-free requirement.
While my kids may want to consume peanut butter sandwiches while they code, hearing that they’re “coding” by telling me how to make them wouldn’t go over well. They want to turn ScratchJr purple and make him curse and jump. They want some form of pixels and plastic to beep and whir and zing. They do not want to watch their mother botch sandwich making because of their bad directions.
Enter mTiny, Makeblock’s cube-shaped robot for the preschool set. It’s cute. It’s fun. It talks. It twirls and giggles and sings. It’s screen-free but uses the same graphics found in ScratchJr in the form of coded cards.
In addition to the USB-rechargeable mTiny robot — with cute panda ears and tail — the kit comes with 36 coding-instruction cards, which are essentially cardboard versions of the ScratchJr graphics. To build codable scenes for mTiny to navigate, Makeblock includes 24 themed, reversible map blocks that kids put together like jigsaw pieces.
More read via https://www.engadget.com/2019/11/17/mtiny-screen-free-coding-robot-review-stem-toy/
The Logistics sector has always been one of the most growing sectors and a laggard in the adoption of technology.
The Logistics sector has always been one of the most growing sectors and a laggard in the adoption of technology. But the advent of latest technologies like IoT, Artificial Intelligence (AI), and Machine Learning (ML) have set this sector on a path, which is soon going to not just transform the sector but also will give rise to a whole new breed of paradigms. Now, as the demand for logistics companies is growing, the driver’s safety has become a primary concern.
With the apps like fleet management system (FMS), it is possible to observe driver’s behaviour in real-time and make a training plan which can also solve the issue of employee’s long driving hours and breaks between drives with fully automated fleets. The availability of sensors and Bluetooth wireless technologies in the trucks have made it easier to add trucks to this burgeoning online network of supply chain data, providing last-mile visibility that was previously unattainable.
Logistics companies are using GPS systems and AI to track the location of their trucks, they can now set up geofences to enable alerts when a truck is nearing its destination, danger, optimise routes using real-time traffic data, improve vehicle utilisation, and automatically track driver hours and fuel tax reporting information. A user-generated input via smartphones is sent onto the drivers which helps them to know the route around construction or congested areas. So that they can avoid these routes and take an alternative route.
Firms have started using this technology for Fuel optimisation, Operational Planning & allocation based on Geospatial & status data, dynamic route management and control. In situations like human errors, traffic or accidents, AI predicts decisions based on data analysis and help to avoid accidents and maintain their safety.
Full Post you can read Via https://www.financialexpress.com/industry/technology/how-artificial-intelligence-is-transforming-logistics-sector/1765595/
Trending factors that will influence the progress of the Global Artificial Intelligence in Diabetes Management Market.
Artificial Intelligence in Diabetes Management Market 2019 research report presents analysis of market size, share, and growth, trends, cost structure, statistical and comprehensive data of the global market. The Market report offers noteworthy data regarding industry’s growth parameters, the current state of the market in terms of analysis of possible economic situations and macroeconomic analysis. This report features competitive scenarios from the recent technology and provides a comprehensive analysis of key growth strategies adopted by key players.
The report has been accumulated through meticulous primary and secondary research, which encompasses interviews, inspections, and observations of experienced analysts, as well as proven paid sources, news articles, annual reports, trade journals, and company body databases. The study also presents a qualitative and quantitative evaluation by analyzing the data collected from industry professionals and market participants across crucial factors in the industry’s value chain. These segments are studied in detail for the market estimates and forecasts at regional and country level.
This report focuses on the Artificial Intelligence in Diabetes Management Market outlook, future outlook, growth opportunities and core and core contacts. The purpose of the study is to present market developments in the US, Europe and other countries. It also analyzes industrial development trends and marketing channels. Industry analysis was conducted to investigate the impact of various factors and to understand the overall appeal of the industry.
Reasons for buying this report:
- It offers an analysis of changing competitive scenario.
- For making informed decisions in the businesses, it offers analytical data with strategic planning methodologies.
- It offers a seven-year assessment of the Global Artificial Intelligence in Diabetes Management Market.
- It helps in understanding the major key product segments.
- Researchers throw light on the dynamics of the market such as drivers, restraints, trends, and opportunities.
- It offers a regional analysis of the Global Artificial Intelligence in Diabetes Management Market along with the business profiles of several stakeholders.
- It offers massive data about trending factors that will influence the progress of the Global Artificial Intelligence in Diabetes Management Market.
A detailed outline of the Global Artificial Intelligence in Diabetes Management Market includes a comprehensive analysis of different verticals of businesses. North America, Latin America, Asia-Pacific, Africa, and Europe have been considered for the studies on the basis of several terminologies.
To know more https://tinyurl.com/ye572xqv