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"I will be sharing about our Pinball Machine Mayhem that is happening in our Technology and Innovation class. We started with a brainstorming session on the process this week. We began with the Project Idea phase: This is where we explained that they would be making pinball machines. How they made them or what they used is completely up to them during this process. Next we moved into the Prototype Design students during this phase was given a blank piece of paper about the size of the actual pinball machines that they will make. The goal here was for them to start to apply the different pieces of their pinball machines to this document. What was incredible about this whole process was before we released the students to go work we asked them what subjects do they think will be covered throughout this process. Right away hands went up and students started sharing. Math - Area, Perimeter, Height, Length, Pythagorean Theorem to find the slope of their machine. ELA - Research, Creating a story for their pinball machine Social Studies - History of the pinball machine, Research on different pinball machines Science - Volume, Friction, Gravity, Art - Theme of their board, Creative look of their pinball machine. Tech Ed - Lights, sensors, buzzers Makerspace - Students talked about using little bits, robotic kits, makey makey board, along with legos and Knex's"

"The groundwork for machine learning was laid down in the middle of last century. But increasingly powerful computers - harnessed to algorithms refined over the past decade - are driving an explosion of applications in everything from medical physics to materials, as Marric Stephens discovers When your bank calls to ask about a suspiciously large purchase made on your credit card at a strange time, it's unlikely that a kindly member of staff has personally been combing through your account. Instead, it's more likely that a machine has learned what sort of behaviours to associate with criminal activity - and that it's spotted something unexpected on your statement. Silently and efficiently, the bank's computer has been using algorithms to watch over your account for signs of theft. Monitoring credit cards in this way is an example of "machine learning" - the process by which a computer system, trained on a given set of examples, develops the ability to perform a task flexibly and autonomously. As a subset of the more general field of artificial intelligence (AI), machine-learning techniques can be applied wherever there are large and complex data sets that can be mined for associations between inputs and outputs. In the case of your bank, the algorithm will have analysed a vast pool of both legitimate and illegitimate transactions to produce an output ("suspected fraud") from a given input ("high-value order placed at 3 a.m."). But machine learning isn't just used in finance. It's being applied in many other fields too, from healthcare and transport to the criminal-justice system. Indeed, Ge Wang - a biomedical engineer from the Rensselaer Polytechnic Institute in the US who is one of those pioneering its use in medical imaging - believes that when it comes to machine learning, we're on the cusp of a revolution."

"What happens to a bowling ball after you bowl with it? How do vending machines really work? What happens to your luggage when you check it in at the airport? What's inside a street organ? In 2017, Centre Pompidou museum approached me to create five short films for their kids web show Mon Œil in line with Preposterous. Les machines impossible series (Impossible Machines), a tribute to Rube Goldberg, explores and reinvents what's inside complex mechanisms. Watch four amusing imaginings from French motion designer Florent Porta: Les machines impossibles - Bowling, above, Soda, Bagage, and Musique:"

"From the creators of Simple Machines and The Robot Factory, comes a fun way for your kids to build awesome stuff in The Everything Machine by Tinybop. If your children are interested in machines, mechanics, programming, or even circuitry at an early age, then encourage them with this fun new tool."

"Video Time Machine is an extremely slick little app that serves up videos from any year from 1860 to 2011. Honestly, if you're interested in popular culture throughout the decades Video Time Machine will keep you entertained for many hours. With over 10,000 videos to find and enjoy, and with support for Airplay and social media sharing, Video Time Machine is a real gem."

"This basketball, simple machine, and mechanism-filled Rube Goldberg Machine is powered by the work of students from Georgia Tech's colleges of Industrial Design and Music, and some signature Globetrotters magic courtesy of 'Buckets' Blakes. The Trick Shot Machine, also scored by the Tech students, is a promo project for the legendary Harlem Globetrotters, filmed before their Atlanta, Georgia games on March 3 and 10, 2018."

"While Macs have a great reputation for being stable and rarely experiencing major issues, the reality is that sometimes things can go wrong. Typically this happens when either a hard drive fails or an OS X system update goes completely awry, but if you have set up Time Machine backups on the Mac like all users should, then you will discover that restoring an entire systems hard drive from that Time Machine backup is really quite easy."

"Computational thinking is the thought processes involved in formulating a problem and expressing its solution(s) in such a way that a computer - human or machine - can effectively carry out. Informally, computational thinking describes the mental activity in formulating a problem to admit a computational solution.  The solution can be carried out by a human or machine. This latter point is important.  First, humans compute.  Second, people can learn computational thinking without a machine.  Also, computational thinking is not just about problem solving, but also about problem formulation.1 The Digital Careers organisation says that students need experience and skills in computational thinking and computer programming (coding) to be successful in their future careers.2 The NSW syllabuses provide a range of opportunities to develop students' understanding of computational thinking and coding. This guide draws out the areas where computational thinking can be applied within the existing NSW K-8 syllabuses. Like the syllabuses, it is organised into stages of learning and subdivided into learning areas, with suggested activities and links to online resources. Not all resources and activities listed in this guide refer to coding explicitly, but they do aim to develop algorithmic and computational thinking skills to better enable students and teachers to reach a coding goal."

Golems is a 3D Physics and Artificial Intelligence simulator. Golems lets you construct a machine - any type of machine - and then bring that machine to life

"A makerspace is a collaborative work space inside a school, library or separate public/private facility for making, learning, exploring and sharing that uses high tech to no tech tools.  These spaces are open to kids, adults, and entrepreneurs and have a variety of maker equipment including 3D printers, laser cutters, cnc machines, soldering irons and even sewing machines.  A makerspace however doesn't need to include all of these machines or even any of them to be considered a makerspace.  If you have cardboard, legos and art supplies you're in business.  It's more of the maker mindset of creating something out of nothing and exploring your own interests that's at the core of a makerspace.  These spaces are also helping to prepare those who need the critical 21st century skills in the fields of science, technology, engineering and math (STEM).  They provide hands on learning, help with critical thinking skills and even boost self-confidence.  Some of the skills that are learned in a makerspace pertain to electronics, 3d printing, 3D modeling, coding, robotics and even woodworking,   Makerspaces are also fostering entrepreneurship and are being utilized as incubators and accelerators for business startups.  There have already been some amazing success stories that have come out of makerspaces to date. "

"In the last few years, machine learning applications have quietly entered every aspect of life: social media to speech recognition, radiology to retail, warfare to writing articles, coding to customer service, robotics to route optimization. During the 40 year information age, we told computers what to do. With advances in artificial intelligence, particularly machine learning, and faster processing chips we can feed computers giant data sets and they can (in narrow slivers) draw some inferences on their own. As we reported in Ask About AI, the rise of code that learns marks the beginning of a new era of augmented intelligence. It's a great opportunity for us to expand access to a great education and for young people to make a big contribution. Given the importance of relationships in human development, AI will augment rather than replace the work of educators in many ways. We'll all have to get better at collaborating with teams that include smart machines. In other professions, augmentation will lead to automation with the potential for significant dislocation. Amazon's workforce, for example, is about 20% robots."

Machines are already superintelligent on many axes, including memory and processing speed. Unfortunately, those are the attributes our education system currently rewards, with an emphasis on learning by rote. It doesn't make sense to me. Part of my job as an investor is to attempt to predict the future - I need to make bets on the way we'll be behaving in the next two, five, ten and 20 years. Computers already store facts faster and better than we do, but struggle to perfect things we learn as toddlers, such as dexterity and walking. We need to rethink the way we teach our children and the things we teach them. Creativity will be increasingly be the defining human talent. Our education system should emphasise the use of human imagination to spark original ideas and create new meaning. It's the one thing machines won't be able to do.