Debris field found — the crew perished in a catastrophic implosion. What are the lessons to be learned from this? How does this apply to future space, stratospheric, and oceanic tourism?
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[Prof. Marvin Minsky] is a very well-known figure in the field of computing, having co-founded the MIT AI lab, published extensively on AI and computational intelligence, and, let’s not forget, inventing the confocal microscope and, of course, the useless machine. But did you know he also was a co-developer of the first Logo “turtle,” and developed a computer intended to run Logo applications in an educational environment? After dredging some PDP-10 tapes owned by the MIT Media Lab, the original schematics for his machine, the Turtle Terminal TT2500 (a reference to the target price of $2500, in 1970 terms), are now available for you to examine.
The machine itself was created in an interesting way; by affixing discrete socketed TTL chips to a large panel, some three hundred or so, the interconnect was performed automatically using a computer-controlled wiring machine that read the design from magnetic tape. The 2,500 used 16-bit user-definable instructions read from a tiny 4k control store. Instruction microcode was read from a 1k microcode store backed up with 64k of RAM. Unusually, it sported a dual display configuration, with one text display and a second vector display for rendering real-time graphics. The machine was intended to run the Logo programming language developed by [Seymour Papert] and others, but this was impossible due to its tiny control store. Instead, it became a display terminal for a connected computer with sufficient resources. You can read more about this fascinating period of time in AI, the life of [Minsky], and others in this New Yorker article.
[Lars Brinkhoff] has created a simulation of the TT2500 running atop a PDP11/45 emulator, a demo of which can be seen below. What a fun story! We covered the passing of the great man back in 2016, which is well worth another read, we reckon. If you want to relive the useless machine, we’ve seen them ranging from the simple to the complex.
Qualcomm Technologies, Inc. unveiled the Qualcomm Video Collaboration Platform, a new suite of video collaboration solutions that allows original equipment manufacturers (OEMs) to easily design and deploy video conferencing products featuring superior video, audio and customizable on-device AI to power engaging, immersive virtual meeting experiences across enterprise, healthcare, educational, and home environments. The Qualcomm® Video Collaboration Platform is a one-stop solution that provides essential hardware and software features specifically tailored for video conferencing so that customers can quickly design and deploy a wide variety of video conferencing products, from enterprise video collaboration systems and huddle room systems to digital whiteboards, to touch controllers and personal devices for the home.
With support for Android and Linux, the three AI-rich platforms offer greater flexibility and ability to customize and deploy video conferencing products across diverse environments. Qualcomm Technologies’ industry-leading innovations in connectivity, compute, AI, audio, and video work together to deliver features that eliminate distractions, enhance productivity, and allow remote meeting callers to feel more connected to conference room participants by providing individual views of everybody in the room, creating an equal viewing experience for all participants.
With the rapid advances in generative AI, future meeting experiences will offer even more advanced video, speech, and text capabilities. Collaboration devices with dedicated hardware support for on-chip AI acceleration will be able to optimize these experiences by splitting workloads between the cloud and edge-based device.
Scientists have taken a significant step forward in the study of the properties of quarks and gluons, the particles that make up atomic nuclei, by resolving a long-standing issue with a theoretical calculation method known as “axial gauge.” MIT
MIT is an acronym for the Massachusetts Institute of Technology. It is a prestigious private research university in Cambridge, Massachusetts that was founded in 1861. It is organized into five Schools: architecture and planning; engineering; humanities, arts, and social sciences; management; and science. MIT’s impact includes many scientific breakthroughs and technological advances. Their stated goal is to make a better world through education, research, and innovation.
The haze of smoke from Canadian wildfires that smothered New York and New England in dark clouds Tuesday night is expected to linger throughout the week, and intensify in some areas as officials urge residents to stay inside and schools cancel outdoor activity amid “unhealthy” and “hazardous” air-quality levels.
New York City
Officials warn pollutants in the air can cause difficulty breathing, headaches and fatigue, and can be unhealthy, especially for people with respiratory illnesses.
The current education landscape requires close collaboration between edtech and AI developers to leverage their expertise and maximize the impact of AI technology in the sector. It also aims to avoid the negative consequences of redundant efforts, wasted resources and less effective solutions. By effectively applying best practices such as clear communication, alignment of goals, and interdisciplinary collaboration, edtech and AI developers can develop innovative, scalable and effective solutions. The “AI and the Future of Learning: Expert Panel Report” underscores key strategies for successful collaboration between edtech and AI developers. The report highlights key strengths and weaknesses of AI as well as the respective opportunities and barriers to employing AI technologies in the education sector.
Education plays a critical role in promoting social and economic development in a region, and when communities recognize its potential, they are more likely to support educational reforms. These reforms can address any challenges in the sector, such as funding constraints, lack of access to quality education and cultural attitudes that may deny education to particular groups. With the increased adoption of AI in the education sector, potential future developments—including ITS, adaptive assessment, gamification and the use of machine learning—can promote the efficiency of personalized learning.
In the long run, the collaboration between edtech and AI developers holds great potential for transforming education and improving learning outcomes. For this to happen, it is necessary to establish industry standards for AI in education, foster interdisciplinary collaboration between educators and AI experts, and invest in research on AI’s impact on learning outcomes. In this way, we can ensure that AI-powered tools are used effectively and ethically to improve student learning in the 21st century.