Mashable Selects Look Up Say More Versus Creator Hub Switch Off Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Trending Now Safety Net In My Bag VidCon with Mashable Back to School All Series'House of the Dragon' Season 3 foreshadowed its saddest finale moment Shannon Connellan is Mashable's Senior Editor, General Assignments, based in London. She has been Mashable's UK Editor (and still manages the illustrious UK team) and Australia Editor, but emotionally, she lives searching for . A Tomatometer-approved critic, Shannon writes about entertainment, tech, social good, science, culture, and Australian horror, and loves to nerd out with movie stars, filmmakers, and TV creators . All products featured here are independently selected by our editors and writers. If you buy something through links on our site, Mashable may earn an affiliate commission.

A screen displays stock market index data as traders work on the floor at the New York Stock Exchange in New York City on Tuesday. A screen displays stock market index data as traders work on the floor at the New York Stock Exchange in New York City on Tuesday. S&P 500 shot up 1.8% and the main measure of Wall Street's health topped its prior all-time high set a few months ago Tue 4 Aug 2026 16.56 EDTLast modified on Tue 4 Aug 2026 18.03 EDT The US stock market rallied to records on Tuesday as profits kept piling up for companies and as oil prices eased. The S&P 500 shot up 1.8%, and the main measure of Wall Street's health topped its prior all-time high set a couple months ago. The Dow Jones industrial average added 907 points, or 1.7%, to its own record set the day before, while the Nasdaq composite jumped 2.6%.

In the data-center age, the business of tech companies is more like oil-refining than coding. The AI boom has showered some of the nation's most prominent companies in market value. OpenAI and Anthropic are now the two most valuable private companies in the world. Google, Microsoft, and Nvidia have become larger than ever. But among the biggest winners has been Caterpillar, a purveyor of yellow trucks and cranes.

Horrifying next twist in the Alexander brothers case: MAUREEN CALLAHAN exposes an unthinkable perversion that's been hiding in plain sight Hollywood icon who starred in Psycho after Hitchcock dubbed her'my new Grace Kelly' looks incredible at 95 Alexander brothers' alleged HIGH SCHOOL gang rape video: Classmates speak out on sick'taking turns' footage... as creepy unseen photos are exposed Model Cindy Crawford, 60, mocked for her'out of touch' morning routine: 'Nothing about this is normal' Kentucky mother and daughter turn down $26.5MILLION to sell their farms to secretive tech giant that wants to build data center there Tucker Carlson erupts at Trump adviser as she hurls'SLANDER' claim linking him to synagogue shooting NFL superstar Xavier Worthy spills all on Travis Kelce, the Chiefs' struggles... and having Taylor Swift as his No 1 fan Heartbreaking video shows very elderly DoorDash driver shuffle down customer's driveway with coffee order because he is too poor to retire Amber Valletta, 52, was a '90s Vogue model who made movies with Sandra Bullock and Kate Hudson, see her now Nancy Mace throws herself into Iran warzone as she goes rogue on Middle East rescue mission: 'I AM that person' It might sound like a gardener's worst nightmare - but'very hungry caterpillars' should be left to feast on plants this spring, conservationists say. Experts are warning that moths, which caterpillars grow into, have seen their numbers plummet by a third since the 1960s. The insects, which are vital pollinators, are struggling with climate change, pollution and an increasingly built-up Britain. Now, the Royal Horticultural Society (RHS) and The Wildlife Trusts are urging green-fingered households to put up with plants being nibbled by caterpillars in order to boost numbers. They explained that caterpillars need plenty of energy to get plump, ready for transformation into a moth.

Experiment in one of the world's quietest rooms reveals the hairs detect airborne sounds--like predators. Breakthroughs, discoveries, and DIY tips sent six days a week. Have you ever walked into a room full of caterpillars? While the answer for most people is probably no, those of us who have may have noticed the insects reacting to the sound of your voice. That's what happened to Carol Miles, a biologist at Binghamton University in New York.

The United Nations special rapporteur on the situation of human rights in the occupied Palestinian territory (oPt) has released a new report mapping the corporations aiding Israel in the displacement of Palestinians and its genocidal war on Gaza, in breach of international law. Francesca Albanese's latest report, which is scheduled to be presented at a news conference in Geneva on Thursday, names 48 corporate actors, including United States tech giants Microsoft, Alphabet Inc. – Google's parent company – and Amazon. A database of more than 1000 corporate entities was also put together as part of the investigation. "[Israel's] forever-occupation has become the ideal testing ground for arms manufacturers and Big Tech – providing significant supply and demand, little oversight, and zero accountability – while investors and private and public institutions profit freely," the report said. "Companies are no longer merely implicated in occupation – they may be embedded in an economy of genocide," it said, in a reference to Israel's ongoing assault on the Gaza Strip.

We introduce novel null models for assessing the results obtained from observed binary transactional and sequence datasets, using statistical hypothesis testing. Our null models maintain more properties of the observed dataset than existing ones. Specifically, they preserve the Bipartite Joint Degree Matrix of the bipartite (multi-)graph corresponding to the dataset, which ensures that the number of caterpillars, i.e., paths of length three, is preserved, in addition to other properties considered by other models. We describe Alice, a suite of Markov chain Monte Carlo algorithms for sampling datasets from our null models, based on a carefully defined set of states and efficient operations to move between them. The results of our experimental evaluation show that Alice mixes fast and scales well, and that our null model finds different significant results than ones previously considered in the literature.

A tournament is a method to decide the winner in a competition, and describes the overall sequence in which matches between the players are held. While deciding a worthy winner is the primary goal of a tournament, a close second is to maximize the value generated for the matches played, with value for a match measured either in terms of tickets sold, television viewership, advertising revenue, or other means. Tournament organizers often seed the players -- i.e., decide which matches are played -- to increase this value. We study the value maximization objective in a particular tournament format called Challenge the Champ. This is a simple tournament format where an ordering of the players is decided. The first player in this order is the initial champion. The remaining players in order challenge the current champion; if a challenger wins, she replaces the current champion. We model the outcome of a match between two players using a complete directed graph, called a strength graph, with each player represented as a vertex, and the direction of an edge indicating the winner in a match. The value-maximization objective has been recently explored for knockout tournaments when the strength graph is a directed acyclic graph (DAG). We extend the investigation to Challenge the Champ tournaments and general strength graphs. We study different representations of the value of each match, and completely characterize the computational complexity of the problem.

Significant progress has been made in advancing large multimodal conversational models (LMMs), capitalizing on vast repositories of image-text data available online. Despite this progress, these models often encounter substantial domain gaps, hindering their ability to engage in complex conversations across new domains. Recent efforts have aimed to mitigate this issue, albeit relying on domain-specific image-text data to curate instruction-tuning data. However, many domains, such as agriculture, lack such vision-language data. In this work, we propose an approach to construct instruction-tuning data that harnesses vision-only data for the agriculture domain. We utilize diverse agricultural datasets spanning multiple domains, curate class-specific information, and employ large language models (LLMs) to construct an expert-tuning set, resulting in a 70k expert-tuning dataset called AgroInstruct. Subsequently, we expert-tuned and created AgroGPT, an efficient LMM that can hold complex agriculture-related conversations and provide useful insights. We also develop AgroEvals for evaluation and compare {AgroGPT's} performance with large open and closed-source models. {AgroGPT} excels at identifying fine-grained agricultural concepts, can act as an agriculture expert, and provides helpful information for multimodal agriculture questions. The code, datasets, and models are available at https://github.com/awaisrauf/agroGPT.

With the recent Nobel Prize awarded for radical advances in protein discovery, foundation models (FMs) for exploring large combinatorial spaces promise to revolutionize many scientific fields. Artificial Life (ALife) has not yet integrated FMs, thus presenting a major opportunity for the field to alleviate the historical burden of relying chiefly on manual design and trial-and-error to discover the configurations of lifelike simulations. This paper presents, for the first time, a successful realization of this opportunity using vision-language FMs. The proposed approach, called Automated Search for Artificial Life (ASAL), (1) finds simulations that produce target phenomena, (2) discovers simulations that generate temporally open-ended novelty, and (3) illuminates an entire space of interestingly diverse simulations. Because of the generality of FMs, ASAL works effectively across a diverse range of ALife substrates including Boids, Particle Life, Game of Life, Lenia, and Neural Cellular Automata. A major result highlighting the potential of this technique is the discovery of previously unseen Lenia and Boids lifeforms, as well as cellular automata that are open-ended like Conway's Game of Life. Additionally, the use of FMs allows for the quantification of previously qualitative phenomena in a human-aligned way. This new paradigm promises to accelerate ALife research beyond what is possible through human ingenuity alone.