This replication study modifies ALMM, the Adaptive Linear Mapping Model constructed for the next song recommendation, to the news recommendation problem on the MIND dataset. The original version of ALMM computes latent representations for users, last-time items, and current items in a tensor factorization structure and learns a linear mapping from content features to latent item vectors. Our replication aims to improve recommendation performance in cold-start scenarios by restructuring this model to sequential news click behavior, viewing consecutively read articles as (last news, next news) tuples. Instead of the original audio features, we apply BERT and a TF-IDF (Term Frequency-Inverse Document Frequency) to news titles and abstracts to extract token contextualized representations and align them with triplet-based user reading patterns. We also propose a reproducibly thorough pre-processing pipeline combining news filtering and feature integrity validation. Our implementation of ALMM with TF-IDF shows relatively improved recommendation accuracy and robustness over Forbes and Oord baseline models in the cold-start scenario. We demonstrate that ALMM in a minimally modified state is not suitable for next news recommendation.

Recently there has been a proliferation of intrinsic motivation (IM) reward-shaping methods to learn in complex and sparse-reward environments. These methods can often inadvertently change the set of optimal policies in an environment, leading to suboptimal behavior. Previous work on mitigating the risks of reward shaping, particularly through potential-based reward shaping (PBRS), has not been applicable to many IM methods, as they are often complex, trainable functions themselves, and therefore dependent on a wider set of variables than the traditional reward functions that PBRS was developed for. We present an extension to PBRS that we prove preserves the set of optimal policies under a more general set of functions than has been previously proven. We also present {\em Potential-Based Intrinsic Motivation} (PBIM) and {\em Generalized Reward Matching} (GRM), methods for converting IM rewards into a potential-based form that are useable without altering the set of optimal policies. Testing in the MiniGrid DoorKey and Cliff Walking environments, we demonstrate that PBIM and GRM successfully prevent the agent from converging to a suboptimal policy and can speed up training. Additionally, we prove that GRM is sufficiently general as to encompass all potential-based reward shaping functions. This paper expands on previous work introducing the PBIM method, and provides an extension to the more general method of GRM, as well as additional proofs, experimental results, and discussion.

Considering Perplexity's bold ambition and the investment it's taken from Jeff Bezos's family fund, NVIDIA, and famed investor Balaji Srinivasan, among others, it's surprisingly unclear what the AI search startup actually is. Earlier this year, speaking to WIRED, Aravind Srinivas, Perplexity's CEO, described his product--a chatbot that gives natural-language answers to prompts and can, the company says, access the internet in real time--as an "answer engine." A few weeks later, shortly before a funding round valuing the company at a billion dollars was announced, he told Forbes, "It's almost like Wikipedia and ChatGPT had a kid." More recently, after Forbes accused Perplexity of plagiarizing its content, Srinivas told the AP it was a mere "aggregator of information." The Perplexity chatbot itself is more specific.

The world's richest tech billionaires increased their fortunes by 750 billion last year - with Amazon founder Jeff Bezos and Facebook tsar Mark Zuckerberg topping the list. Forbes has released its annual roster of the world's wealthiest technology tycoons - and the profit increases they saw in 2023 are eye-watering. Bezos, 60, added 80 billion to his net worth, while Zuckerberg, 39, enjoyed a whopping 113 billion increase to his net value. Of the planet's 342 billionaires who made their fortune in the tech industry - earning a combined income of 2.6 trillion last year - Bezos tops the list. Bezos' net worth surged 80 billion to 194 billion in 2023, according to Forbes.

An interactive exhibit opening Wednesday at the National WWII Museum will use artificial intelligence to let visitors hold virtual conversations with images of veterans, including a Medal of Honor winner who died in 2022. Voices From the Front will also enable visitors to the New Orleans museum to ask questions of war-era home front heroes and supporters of the U.S. war effort -- including a military nurse who served in the Philippines, an aircraft factory worker, and Margaret Kerry, a dancer who performed at USO shows and, after the war, was a model for the Tinker Bell character in Disney productions. Four years in the making, the project incorporates video-recorded interviews with 18 veterans of the war or the support effort -- each of them having sat for as many as a thousand questions about the war and their personal lives. Among the participants was Marine Corps veteran Hershel Woodrow "Woody" Wilson, a Medal of Honor Winner who fought at Iwo Jima, Japan. He died in June 2022 after recording his responses.

Cruise, General Motors' driverless car subsidiary, will soon lay off employees. According to Forbes, the company's CEO Kyle Vogt told staff of the decision in an all-hands meeting earlier this week. Cruise hasn't yet decided who or how many people will lose their jobs, Vogt said, but promised to provide more details in the next three weeks. The company will also conduct internal "listening sessions", and explore building websites detailing collisions Cruise cars are involved in, Forbes said. The news comes on the heels of multiple crises facing the company since October after a Cruise robotaxi dragged a San Francisco pedestrian thrown into its path more than 20 feet before braking to a halt.

Accurate, self-consistent bathymetric maps are needed to monitor changes in subsea environments and infrastructure. These maps are increasingly collected by underwater vehicles, and mapping requires an accurate vehicle navigation solution. Commercial off-the-shelf (COTS) navigation solutions for underwater vehicles often rely on external acoustic sensors for localization, however survey-grade acoustic sensors are expensive to deploy and limit the range of the vehicle. Techniques from the field of simultaneous localization and mapping, particularly loop closures, can improve the quality of the navigation solution over dead-reckoning, but are difficult to integrate into COTS navigation systems. This work presents a method to improve the self-consistency of bathymetric maps by smoothly integrating loop-closure measurements into the state estimate produced by a commercial subsea navigation system. Integration is done using a white-noise-on-acceleration motion prior, without access to raw sensor measurements or proprietary models. Improvements in map self-consistency are shown for both simulated and experimental datasets, including a 3D scan of an underwater shipwreck in Wiarton, Ontario, Canada.

Here's a question that's been percolating since ChatGPT abruptly entered the mainstream: Does AI provide more avenues to enhance and augment education, or drive it into obsolescence? According to Under 30 Europe lister Joel Hellermark, the future of artificial intelligence and machine learning is rife with possibilities that can help the ways in which humans learn and collaborate, not replace them. He offered the calculator as a comparison: "If we think about it just like an insanely powerful calculator, you'd want everyone to just learn to use the calculator. Why should you sit there and do a bunch of calculations? The 26-year-old cofounder of software company Sana Labs has been immersed in the coding space since taking online Stanford courses at just 13 years old in Sweden. Now, at his startup, he's built an AI-driven software to help businesses manage workforce onboarding and training. The program pulls from correspondences, documents and the internet to answer questions and help train employees. Sana introduced the product to the world just as it was shutting down in 2020, and initially offered their platform to hospitals free of charge (over 2,000 took them up on the offer). Sana has since landed paying clients, including Klarna, Merck and Electrolux, and has raised $54.5 million. Hellermark, who dropped out of school at 19 to start the company, envisions a near future where the content we interact with is presented to us dynamically and with our personal contexts in play. "We're so used to creating content and then someone consumes the exact thing that you created– that goes all the way back to the printing press," says Hellermark. "It hasn't changed that much since.

In another sign that the current VC appetite for AI is insatiable, Adept, a startup building AI that "enables humans and computers to work together creatively to solve problems," yesterday announced that it raised $350 million in a Series B funding round co-led by General Catalyst and Spark Capital with participation from Addition, Greylock, Atlassian Ventures, Microsoft, Nvidia, Workday Ventures, Caterina Fake, Frontiers Capital, PSP Growth, SV Angel and A.Capital. Forbes reports that the valuation was "at least" $1 billion. The cash injection brings Adept's total raised to $415 million, which co-founder and CEO David Luan says is being put toward productization, model training and headcount growth. "Giant foundation models for language and for images have shown astounding capabilities in the last few years. Adept is building on this momentum via a new kind of foundation model that can perform actions on any software tool using natural language," he said in a press release.

When co-founders Larry Page and Sergey Brin announced that they were leaving their day-to-day roles at Google parent Alphabet in 2019, handing Sundar Pichai the keys to the kingdom, they mused about Google's age. "If the company was a person, it would be a young adult of 21 and it would be time to leave the roost," they wrote. "We believe it's time to assume the role of proud parents--offering advice and love, but not daily nagging!" Four years later, as Google faces incursions from AI rivals dead set on dethroning the company's iconic search business, the absent parents have returned home. Microsoft, a once-dormant rival, has sprung to life with a new version of Bing, aided by OpenAI, the upstart maker of the generative AI bot ChatGPT.