Determining the capacity $\alpha_c$ of the Binary Perceptron is a long-standing problem. Krauth and Mezard (1989) conjectured an explicit value of $\alpha_c$, approximately equal to .833, and a rigorous lower bound matching this prediction was recently established by Ding and Sun (2019). Regarding the upper bound, Kim and Roche (1998) and Talagrand (1999) independently showed that $\alpha_c$ < .996, while Krauth and Mezard outlined an argument which can be used to show that $\alpha_c$ < .847. The purpose of this expository note is to record a complete proof of the bound $\alpha_c$ < .847. The proof is a conditional first moment method combined with known results on the spherical perceptron

Computational sciences in the India region are going through an exciting time. While India has always had significant strength in theoretical computer science (CS), in recent years it has developed substantial presence and maturity in other, more applied areas of CS such as hardware and computer architecture, data science and artificial intelligence (AI), and cyber-security. Alongside pure research, there has been a significant push toward lab-to-field projects and technology transfer and deployment, creating broad impact to the region and beyond. Significant efforts have been made on the democratization of education through online courses, enabling the vast population to learn from a relatively limited number of available experts. All these activities have continued to bolster India's already strong IT industry and been a factor in the huge increase in the number of startups (under 1,000 in 2016 to over 60,000 in 2022a), with the number of unicorn startups reaching 100.b

Professor Yang-Hui He is a Fellow of the London Institute for Mathematical Sciences, professor of mathematics at City, University of London, Lecturer in mathematics at Merton College, Oxford, and Chang-Jiang Chair of physics at Nankai University in China. He obtained his BA at Princeton (summa cum laude, Shenstone Prize and Kusaka Prize), MA at Cambridge (Distinction, Tripos), and PhD at MIT. After a postdoc at the University of Pennsylvania, he joined Oxford as the FitzJames Fellow and an STFC Advanced Fellow. He works at the interface of string theory, algebraic and combinatorial geometry, and machine learning. Professor He is the Editor-in-Chief of the International Journal of Data Science in the Mathematical Sciences (World Scientific), and has over 200 journal publications and invited chapters.

Researchers have gained a first insight into how the brain structures higher-level information. By extracting and analysing data from a neural network of grid cells, they found that the collective neural activity is shaped like the surface of a doughnut. The study, from the Norwegian University of Science and Technology's (NTNU) Kavli Institute for Systems Neuroscience and collaborators, is published in Nature, High-level brain functions result from the orchestration of activity between many thousands of neurons in neural networks. For grid cells, these neural network conversations result in our understanding of location, our capacity to navigate, and our mental maps. "This discovery provides one of the first insights into how brain cells operate collectively, as a society. It provides an unprecedented glimpse into how large networks of neurons produce properties that cannot be inferred from the activities of single cells. These collective codes are the clue to all high-level cognitive functions of the brain," said Edvard Moser, a professor of neuroscience and co-director of the Norwegian University of Science and Technology's(NTNU)Kavli Institute for Systems Neuroscience.

As a university student, Abigail Annkah fell in love with mathematics, which soon led to her interest in artificial intelligence. After graduating from the African Institute for Mathematical Sciences, Abigail made it through the competitive process to become an AI resident at Google Research, Accra. After her residency, Google offered her a job and she’s now a research software engineer working on several high-profile projects.As Google grows its presence in Accra, we spoke to Abigail about the mapping project that motivates her, starting a new job while becoming a mother and the importance of inspiring young girls to enter STEM careers.How did your science background lead you to Google?I did my undergraduate degree in Bachelor of Science Statistics at the University of Ghana, finishing with a combined major in Mathematics and Statistics. During the second year of study, I stumbled upon Computational Maths, leading to my first taste of coding. I started taking extra credit courses, which really kickstarted my entry into AI. Then I joined the first cohort of the African Masters of Machine Intelligence program at African Institute for Mathematical Sciences with the support of Google and Facebook. The program intends to bridge the AI education gap in Africa and strengthen the growing data science ecosystem in the region — this was my first exposure to the world of Machine Learning.

The small whale, known for its distinctively spiraled tusk, is under mounting pressure due to warming waters and the subsequent increase in Arctic shipping traffic. To better care for narwhals, we need to learn more about their foraging behaviour – and how these may change as a result of human disturbances and global warming. Biologists know almost nothing about this. Because narwhals live in isolated Arctic regions and hunt at depths of up to 1,000 meters, it is very difficult – sometimes impossible – to gain any insight whatsoever. Ironically, artificial intelligence may be the answer to the mystery of their natural behaviours.

The first dedicated masters degree program for machine intelligence in Africa is launching in September with backing from tech leaders Google and Facebook. The African Institute for Mathematical Sciences (AIMS), which created the program, says the African Masters of Machine Intelligence (AMMI) is crucial so African countries don't get left behind as advancements in machine intelligence rapidly develop. "The lack of MI researchers from Africa means that many opportunities to use MI to create a better and more stable world are being missed," said Moustapha Cissé, founder of the program. He noted Africa is on the lower end of a "technology gap" in the field. This is why the program is called the "African Masters" in machine intelligence, as a branding strategy but also because the challenges they are choosing to focus on in the program will be challenges and insights relevant to Africa.

In an analysis that investigated and built upon several recent studies on the topic, researchers found that about half of jobs are at risk, with automation targeting low-wage, low-skilled positions in particular. In an analysis that investigated and built upon several recent studies on the topic, researchers found that about half of jobs are at risk, with automation targeting low-wage, low-skilled positions in particular. In the new study, the researchers from the Center for Business and Economic Research at Ball State University compared the threat of offshoring and automation in the United States, revealing which jobs and regions in the country are most at risk. In the new study, the researchers from Ball State University compared the threat of offshoring and automation in the United States, revealing which jobs and regions in the country are most at risk.