Education, Looking forward,
The five tips for better experience:
- Sound is more important than picture.
- Look into the camera !
- Don't make the obvious mistakes: Background, lighting, and clothing.
- Be lively! The medium consumes energy; you need to compensate.
- Get to know the tools
- Talk to one student, not many.
- Structure, structure, structure (much more important in online teaching).
- Interaction is possible but needs to be planned.
- Bring a friend: Teach with a colleague, for mutual help and a better experience.
- Use the recording as a tool for making your teaching better, by reviewing it and editing it yourself.
May Grow to Many !
Many people fear that robots and artificial intelligence (AI) systems are going to steal their jobs. To a certain degree, those fears are warranted. According to data from the McKinsey Global Institute, as many as 73 million U.S. jobs could be automated by 2030.
While that is concerning at a surface level, many people ignore the fact that automation is actually a good thing. It keeps workers out of harmful environments, speeds up production lines, and paves the way for better overall opportunities.
Many people are looking for a future-proof position. According to that logic, there is no better job field to enter than that of artificial intelligence. Even if machines take over countless jobs, humans are still necessary to program the algorithms !!
Let go your conscious self and act on instinct
Machine learning engineers are up to the task - and rake in a median salary of $114,000 in US. They are primarily responsible for building and managing these platforms. Those with a background in data science and who are fluent in multiple programming languages are ideal candidates for the role.
A machine learning engineer can expect to work with predictive models, natural language processing, massive data-sets, and a variety of other development tools. In terms of education, most companies look for someone with a master's or doctoral degree in mathematics or computer science.
For individuals without those academic credentials, a position as a regular software developer is a great starting place. This not only lets you gain the programming skills needed, but it also opens the door for valuable experiences with problem-solving and analytical skills.
Data Science : A tool of future research
The data trumps is at the heart of every algorithm and application. As such, individuals who know how to work with data are in high demand. Data science is a broad field, but it is closely intertwined with the AI sector due to the similarities between the two.
Those working as data scientists can expect to earn a median salary of $113,000 per year (in US). However, the positions can not be filled by just anyone. Companies expect that data scientists hold a master's or doctoral degree in computer science.
It's worth noting that being a data scientist could be perfect for someone that is not as interested in programming from scratch. Individuals in data science roles typically work with Big Data tools like Hive, Hadoop, MapReduce, Pig, and Spark. However, that does not mean that programming is not part of the job. In-depth knowledge of languages like Perl, Python, Scala, and SQL is also necessary.
Forbes, Zak Doffman, June 30, 2020
The Israeli military has adopted artificial intelligence (AI), multi-source data fusion, and augmented reality (AR) to weed out terrorists from civilians in urban areas. Similar to Google Street View, the military is using an AR overlay from the fusion of multiple sources of highly classified intelligence and open source data on the terrain and environment, along with AI running pattern analytics from previous combat experiences to gauge the hidden enemy's next move.
The AR display, which is shown to soldiers on a smartphone or tablet or streamed directly into their binoculars or weapons sights, helps them understand why a location has been deemed hostile. Final targeting decisions are left to the soldiers on the ground. The AI tool is tasked with distilling terabytes of intelligence every day into useful and relevant data, and soldiers have just five to 10 seconds to decide on any action t hey take based on that data.
 Source: ACM Technical News.