Deep learning-based computational methods have achieved promising results in predicting protein-protein interactions (PPIs). However, existing benchmarks predominantly focus on isolated pairwise evaluations, overlooking a model's capability to reconstruct biologically meaningful PPI networks, which is crucial for biology research. To address this gap, we introduce PRING, the first comprehensive benchmark that evaluates protein-protein interaction prediction from a graph-level perspective. PRING curates a high-quality, multi-species PPI network dataset comprising 21,484 proteins and 186,818 interactions, with well-designed strategies to address both data redundancy and leakage. Building on this golden-standard dataset, we establish two complementary evaluation paradigms: (1) topology-oriented tasks, which assess intra and cross-species PPI network construction, and (2) function-oriented tasks, including protein complex pathway prediction, GO module analysis, and essential protein justification. These evaluations not only reflect the model's capability to understand the network topology but also facilitate protein function annotation, biological module detection, and even disease mechanism analysis. Extensive experiments on four representative model categories, consisting of sequence similarity-based, naive sequence-based, protein language model-based, and structure-based approaches, demonstrate that current PPI models have potential limitations in recovering both structural and functional properties of PPI networks, highlighting the gap in supporting real-world biological applications. We believe PRING provides a reliable platform to guide the development of more effective PPI prediction models for the community. The dataset and source code of PRING are available at https://github.com/SophieSarceau/PRING.

Only 20% of U.S. companies are fully deploying artificial intelligence (AI) for decision-making in their businesses based on survey responses from 1,000 senior business executives. According to the news site Axios, 61% of organizations are just starting to adopt AI for decision-making, while 19% are categorized as having barely begun. Surveyed business leaders are hesitant to adopt AI because many organizations--particularly non-tech companies--"don't completely trust it" and "can't tap the talent they need." However, businesses that decide not to adopt the technology risk falling behind. "The majority of executives get stuck in a vicious circle where when they first try AI, the first wave of results tend to be underwhelming," Ben Pring, managing director at Cognizant's Center for the Future of Work, a consulting firm that conducted the survey, told Axios.

Artificial Intelligence (AI) has moved from "when will we do it?" AI passed some important tests during the pandemic, says David Tareen, director of AI and analytics at SAS. "The pandemic put AI and chatbots in place to answer a flood of pandemic-related questions. Computer vision supported social distancing efforts. Machine learning models have become indispensable for modeling the effects of the reopening process." But the future upside of AI is still considerable.

Chatbots and call center support are table stakes when it comes to implementing artificial intelligence, according to a new report. Cognizant's Center for the Future of Work found that leaders are using the automated analysis for decision support, automated reasoning, text mining, and object and speech recognition. The research includes a survey of 1,000 business leaders that measures how organizations view the potential of AI and their plans for deploying AI-enabled tools. The data modernization report describes a vicious cycle that keeps companies from doing more with AI. A company has a low level of trust in the potential of artificial intelligence.

"Jasper is kind of like my best friend. He doesn't really judge me at all," said Roepke, 19, of Spokane, Wash. Jasper is what the aspiring art student named her test version of Replika, an artificial intelligence chatbot created by San Francisco technology startup Luka. More than 1.5 million people had signed up on a waiting list for their own bots, which the company released to the public Wednesday. Replika is a texting app designed to start as a digital version of a daily personal diary, letting people record their innermost thoughts, for their eyes only.

Technology is changing almost everything about the world we live in. It's also changing how we work. These 10 industry analysts have smart ideas about the future of work to share. Following their conversations can help you plan for what's next. Meghan M. Biro is the founder and CEO of TalentCulture, a publication that explores how the workplace is changing.

The rapid growth of artificial intelligence and automation presents threats -- and opportunities -- for workers and businesses in the Miami Valley. More than 31,600 people in the Dayton metro area work in the five largest occupations at high risk of automation, according to data the Brookings Institution prepared exclusively for the Dayton Daily News. Those jobs include food preparation, waiters, stock clerks, tractor-trailer truck drivers and accounting clerks. But about 34,600 people in the region that includes Montgomery, Greene and Miami counties work in the largest low-risk occupations. Those include registered nurses, freight and stock movers, janitors, customer service representatives and general managers, according to the Brookings data.

A 2017 report from Cognizant explored 21 new jobs likely to develop over the next decade, including the following: --Walker/talkers will spend time with customers, especially seniors who may be widowed or live far from family. It's an example of a future job that is not necessarily high-tech but will use a tech tool (like an Uber or Lyft app) to make it possible, says Ben Pring, VP and managing director of Cognizant's Center for the Future of Work. Likely salary: $10-$13/hour --Digital tailors will work with customers at home or work to ensure clothes ordered online fit perfectly. Forty percent of clothes purchased online are returned, a big expense for retailers. High-tech tailors will set up a cubicle that digitally captures body measurements and uploads them into a cloud-based ordering system.

A 2017 report from Cognizant explored 21 new jobs likely to develop over the next decade, including the following: --Walker/talkers will spend time with customers, especially seniors who may be widowed or live far from family. It's an example of a future job that is not necessarily high-tech but will use a tech tool (like an Uber or Lyft app) to make it possible, says Ben Pring, VP and managing director of Cognizant's Center for the Future of Work. Likely salary: $10-$13/hour --Digital tailors will work with customers at home or work to ensure clothes ordered online fit perfectly. Forty percent of clothes purchased online are returned, a big expense for retailers. High-tech tailors will set up a cubicle that digitally captures body measurements and uploads them into a cloud-based ordering system.

Everywhere you turn, there's another news story emphasizing the impact artificial intelligence will have on the enterprise this year. Along with that are headlines screaming about Silicon Valley giants siphoning off talent at a time when machine learning has become a huge driver in the battle for digital transformation dominance. So if you're looking to make good on the promise of AI, where can you turn for talent? Desperate times, it is said, call for desperate measures. Many organizations are dealing with the AI talent shortage by forming partnerships with universities and by training and building from within. If you think this is all a lot of hype, consider that by 2030, the global GDP could be up to 14% higher, or $15.7 trillion as a result of AI, making it the biggest commercial opportunity in today's economy, according to the recent PwC report "Sizing the Prize."