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"The combination of ChatGPT with its Wolfram plug-in just scored 96% in a UK Maths A-level paper, the exam taken at the end of school, as a crucial metric for university entrance. (That compares to 43% for ChatGPT alone). If this doesn't shock you, it should. Maths A-level (like its equivalent in many other countries) is held up as the required and essential qualification for much of our populations-the way to be prepared for our upcoming AI age. And yet, here it is, done by those very AIs, better than most of our students."

"Can Artificial Intelligence (Chat GPT) get a 7 on an SL Maths paper?"

"The algorithm behind what3words took six months to write. Sheldrick worked on it with two friends he had grown up with. Mohan Ganesalingham, a maths fellow at Trinity College, Cambridge, and Jack Waley-Cohen, a full-time quiz obsessive and question-setter for Only Connect. After the initial mapping was complete, they incorporated an error-correction algorithm, which places similar-sounding combinations a very long way apart."

""Weapons of math destruction" is how the writer Cathy O'Neil describes the nasty and pernicious kinds of algorithms that are not subject to the same challenges that human decision-makers are. Parole algorithms (not Jure's) can bias decisions on the basis of income or (indirectly) ethnicity. Recruitment algorithms can reject candidates on the basis of mistaken identity. In some circumstances, such as policing, they might create feedback loops, sending police into areas with more crime, which causes more crime to be detected."

"When Fry returned to London, she realised how mathematicians, computer engineers and physicists are so used to working on abstract problems that they rarely stop to consider the ethics of how their work might be used"

"Instead, the new work shows our brains rely on the kind of maths that an algorithm might use to perform the task. In fact, Tsao and her colleague, Steven Le Chang, stumbled on their discovery while working on computer vision. The pair had initially set themselves the challenge of coming up with a way of reliably converting facial images into a numerical representation."

"Bitcoin mining - the process in which a bitcoin is awarded to a computer that solves a complex series of algorithms - is a deeply energy-intensive process. "Mining" bitcoin involves solving complex math problems in order to create new bitcoins. Miners are rewarded in bitcoin. Earlier in bitcoin's relatively short history - the currency was created in 2009 - one could mine bitcoin on an average computer. But the way bitcoin mining has been set up by its creator (or creators - no one really knows for sure who created it) is that there is a finite number of bitcoins that can be mined: 21m. The more bitcoin that is mined, the harder the algorithms that must be solved to get a bitcoin become."

"Half a century ago, before the first Apple computer was even sold, climate scientists started making computer-generated forecasts of how Earth would warm as carbon emissions saturated the atmosphere (the atmosphere is now brimming with carbon). It turns out these decades-old climate models - which used math equations to predict how much greenhouse gases would heat the planet - were pretty darn accurate. Climate scientists gauged how well early models predicted Earth's relentless warming trend and published their research Wednesday in the journal Geophysical Research Letters."

"Therefore even Ofqual's best model significantly worsened grade accuracy for most A-level subjects when the cohort size is below 50, which is common (almost 62% of the total in 2019). For GCSEs, even with larger cohorts, the best model would have worsened the grade accuracy for Maths and Sciences. A very conservative figure of 25% of wrong grades would have amounted to 180,000 wrong A-level grades and 1.25 million wrong GCSE grades."

"Further, human intelligence is the lever that we have used for millennia to create the world we live in today: science, technology, math, physics, chemistry, medicine, energy, construction, transportation, communication, art, music, culture, philosophy, ethics, morality. Without the application of intelligence on all these domains, we would all still be living in mud huts, scratching out a meager existence of subsistence farming. Instead we have used our intelligence to raise our standard of living on the order of 10,000X over the last 4,000 years. What AI offers us is the opportunity to profoundly augment human intelligence to make all of these outcomes of intelligence - and many others, from the creation of new medicines to ways to solve climate change to technologies to reach the stars - much, much better from here."

"A natural alternative to symbolic AI came to prominence: Instead of modeling high-level reasoning processes, why not instead model the brain? After all, brains are the only things that we know for certain can produce intelligent behavior. Why not start with them?"

"That can include statistical or machine learning algorithms that rely on police records detailing the time, location, and nature of past crimes in a bid to predict if, when, where, and who may commit future infractions. In theory, this should help authorities use resources more wisely and spend more time policing certain neighborhoods that they think will yield higher crime rates."