Global reaction to the fall of Assad ranges from jubilation to alarmBritish-Canadian computer scientist Geoffrey Hinton and co-laureate John Hopfield are set to receive the Nobel Prize for physics on Tuesday in Stockholm. The pair landed the accolade because they used physics to develop artificial neural networks, which help computers learn without having to program them. These networks form the foundation of machine learning, a computer science that relies on data and algorithms to help artificial intelligence mimic the human brain. Hinton and Hopfield’s path to the Nobel began when Hopfield, who is now a professor emeritus at Princeton University, invented a network in 1982 that could store and reconstruct images in data. The Hopfield network uses associate memory, which humans use to remember what something looks like when it’s not in front of them or to conjure up a word they know but seldom use. The network can mirror this process because it stores patterns and has a method for recreating them. When the network is given an incomplete or slightly distorted pattern, the method then searches for the stored pattern that is most similar to recreate data. This means if a computer was shown, for example, a photo of dog where only part of the animal was visible, it could use the network to piece together the missing part of the image and recognize it was depicting a dog. Hinton, who was working at Carnegie Mellon University in Pittsburgh in 1985, used the Hopfield network as the foundation for a new network he called the Boltzmann machine. Its name came from the nineteenth-century physicist Ludwig Boltzmann. The Boltzmann machine learns from examples, rather than instructions, and when trained, can recognize familiar characteristics in information, even if it has not seen that data before. The Royal Swedish Academy of Sciences, which gives out the Nobel, likens this to how humans may be able to identify someone as a relative of one of their friends, even if they’ve never met this person before, because of they share similar traits. The Boltzmann machine works in a similar way, classifying images or creating new examples based on the patterns it was trained on. This kind of technology can help suggest films or television shows based on a user’s preferences and past viewing history The Hopfield network and Boltzmann machine are considered to have laid the groundwork for modern AI. Hinton, a professor emeritus at the University of Toronto, went on to win the A.M. Turing Award, known as the Nobel Prize of computing, with fellow Canadian Yoshua Bengio and American Yan LeCun in 2018. He is often called the godfather of AI. This report by The Canadian Press was first published Dec. 8, 2024. Tara Deschamps, The Canadian Press
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So, when MacPaw offered to fly me out to Kyiv, Ukraine, to meet and interview the folks leading Moonlock, its cybersecurity division, I jumped at the opportunity. This interview is divided into three parts: About Moonlock, the technology behind the Moonlock Engine, and what's planned for the future. Disclosure: Ukraine is a country at war. Many members of the Moonlock team also aid in the defense of their country, so false names may be used below to protect their identity. Some parts of the transcript were edited for clarity. You're reading Security Bite, a security-focused column on 9to5Mac. Each week, Arin Waichulis delivers insights and interviews on the latest in data privacy, the current malware landscape, and emerging threats within Apple's vast ecosystem of over 2 billion active devices. At the time of writing, MacPaw's HQ, the very place where this interview was conducted weeks prior, was just severely damaged in a ballistic missile attack. My heart goes out to the team. Thankfully, no one was harmed. Please... Arin WaichulisRealty Income ( O 0.10% ) and Agree Realty ( ADC -0.87% ) are two of the largest real estate investment trusts (REITs) focused on freestanding retail properties secured by net leases. Those leases require tenants to cover all operating expenses (including routine building maintenance, real estate taxes, and property insurance). That enables the REITs to collect very stable rental income, which allows them to pay monthly dividends. Given their similar strategies, most investors will likely only want to own one of these REITs . Here's a look at which of these monthly dividend stocks is the better buy for passive income right now . A look at the numbers It's essential to take a closer look at the key financial metrics of these REITs to see how they compare. Here's a snapshot of those numbers: Monthly Dividend Stock Dividend Yield Dividend Payout Ratio Leverage Ratio 2024 AFFO Growth Rate (midpoint) Price to AFFO Agree Realty 3.9% 73% 3.6x 4.6% 18.7x Realty Income 5.5% 75.1% 5.4x 4.8% 13.7x Data source: Realty Income and Agree Realty. From these numbers, we can see that Realty Income has a much higher dividend yield , which is due solely to its much lower valuation since they both have similar dividend payout ratios . At first glance, the only explanation for the valuation difference is that Agree Realty has a much lower leverage ratio , considering that the REITs are growing their adjusted funds from operations (AFFO) at around the same rate this year. That would seem to imply that Agree Realty is a financially stronger company. However, a closer look at their balance sheets suggests things are much tighter than they appear at first glance. Agree Realty's leverage ratio is 4.9x after excluding unsettled forward equity (stock it agreed to sell to fund future investments). Meanwhile, the REIT's credit rating is BBB+/Baa1, which is a notch below Realty Income's A-/A3 credit rating (it's one of eight REITs in the S&P 500 index with credit ratings that high or better). So, clearly, Realty Income is a very financially strong REIT. A look at their portfolios Realty Income and Agree Realty have similar real estate portfolios since they focus on owning freestanding net lease retail properties. However, there are some key differences between their portfolios. Realty Income owns 15,457 properties around the U.S. and Europe leased to 1,552 clients in 90 industries. It's the seventh-largest REIT in the world, with $58 billion of real estate. Retail properties comprise 79.4% of its portfolio. Realty Income also owns industrial real estate (14.6%), gaming properties (3.2%), and other real estate (including data centers). About 32% of its rent comes from investment-grade tenants. Agree Realty has a much smaller portfolio. The REIT owns 2,271 retail properties around the U.S. While net leases make up the bulk of its portfolio, the REIT also has 223 ground leases that supply about 10.9% of its annual base rent. Ground leases are even more stable than net leases and provide bond-like income. The company gets 67.5% of its rent from investment-grade tenants. From this information, we can glean that Realty Income offers investors a much more diversified portfolio (geographically and by property type). However, Agree Realty has a lower-risk portfolio, given its focus on investment-grade tenants and its ground leases. The better REIT to buy right now While both REITs are great options for those seeking a monthly stream of passive dividend income , Realty Income is the better buy right now. It trades at a much lower valuation (and higher dividend yield) even though it's growing as fast as Agree Realty and has a similarly strong financial profile. While Agree Realty has some lower-risk characteristics, Realty Income also has a low-risk profile and offers investors greater diversification and scale. Realty Income gives investors higher total return potential from its higher yield and lower relative valuation, making it the better buy right now .