In this paper, we propose a Hybrid Multimodal Memory module to address the above challenges.

This is Bloomberg Opinion Today, an updated Bayeux Tapestry of Bloomberg Opinion's opinions. Apple Inc. recently added audiobook narration to the growing list of occupations where algorithms are poised to replace humans alongside graphic designers, college essayists and limerick writers. Luckily, the fine art of newslettering remains (ahem) far beyond the capabilities of even the most sophisticated artificial intelligence software. Still, hope is at hand for those not fortunate enough to toil in the newsletter mines but still seeking gainful employment that won't disappear as robots take control.

The discovery of reusable sub-routines simplifies decision-making and planning in complex reinforcement learning problems. Previous approaches propose to learn such temporal abstractions in a purely unsupervised fashion through observing state-action trajectories gathered from executing a policy. However, a current limitation is that they process each trajectory in an entirely sequential manner, which prevents them from revising earlier decisions about sub-routine boundary points in light of new incoming information. In this work we propose SloTTAr, a fully parallel approach that integrates sequence processing Transformers with a Slot Attention module and adaptive computation for learning about the number of such sub-routines in an unsupervised fashion. We demonstrate how SloTTAr is capable of outperforming strong baselines in terms of boundary point discovery, even for sequences containing variable amounts of sub-routines, while being up to 7x faster to train on existing benchmarks.

Craft.co is a supplier intelligence company helping organizations accelerate data-informed business decisions. Our unique, proprietary data platform tracks thousands of real-time signals across millions of companies globally, delivering best in class monitoring and insight into global supply chains, among other company cohorts. Our clients, including Fortune 100 companies, government and military agencies, SMEs, asset management groups, and others, use our technology for supply chain intelligence, market intelligence and related use cases. Through our modular, secure, customizable portal, our clients can monitor any company they are working with and drive critical actions in real-time. We are a well-funded technology company with leading investors from Silicon Valley and elsewhere, but are not your typical data or SaaS startup.

Craft.co is a supplier intelligence company helping organizations accelerate data-informed business decisions. Our unique, proprietary data platform tracks thousands of real-time signals across millions of companies globally, delivering best in class monitoring and insight into global supply chains, among other company cohorts. Our clients, including Fortune 100 companies, government and military agencies, SMEs, asset management groups, and others, use our technology for supply chain intelligence, market intelligence and related use cases. Through our modular, secure, customizable portal, our clients can monitor any company they are working with and drive critical actions in real-time. We are a well-funded technology company with leading investors from Silicon Valley and elsewhere, but are not your typical data or SaaS startup.

Banking and investing in the years to come are unlikely to resemble what they looked like or how they worked for our grandparents. An enormous amount of data and a high rate of digitization continue to transform the landscape of the financial services sector and how customers engage with it. Ubiquitous and vast varieties of data, combined with the sector's reliance on technology, pose new challenges, threats and vulnerabilities. The newly formed industry-guided research center, the Center for Research toward Advancing Financial Technologies (CRAFT), funded by the National Science Foundation's Industry-University Cooperative Research Center Program, is setting out to leverage the opportunities for advancement and innovation in the industry and to address the many threats and vulnerabilities it faces. At a launch event for CRAFT in the fall of 2021, industry leaders discussed many examples of such pressing challenges and research opportunities.

Craft is a supplier intelligence company helping organizations accelerate data-informed business decisions. Our unique, proprietary data platform tracks thousands of real-time signals across millions of companies globally, delivering best in class monitoring and insight into global supply chains, among other company cohorts. Our clients, including Fortune 100 companies, government and military agencies, SMEs, asset management groups, and others, use our technology for supply chain intelligence, market intelligence and related use cases. Through our modular, secure, customizable portal, our clients can monitor any company they are working with and drive critical actions in real-time. We are a well-funded technology company with leading investors from Silicon Valley and elsewhere, but are not your typical data or SaaS startup.

We propose Continual Repeated Annealed Flow Transport Monte Carlo (CRAFT), a method that combines a sequential Monte Carlo (SMC) sampler (itself a generalization of Annealed Importance Sampling) with variational inference using normalizing flows. The normalizing flows are directly trained to transport between annealing temperatures using a KL divergence for each transition. This optimization objective is itself estimated using the normalizing flow/SMC approximation. We show conceptually and using multiple empirical examples that CRAFT improves on Annealed Flow Transport Monte Carlo (Arbel et al., 2021), on which it builds and also on Markov chain Monte Carlo (MCMC) based Stochastic Normalizing Flows (Wu et al., 2020). By incorporating CRAFT within particle MCMC, we show that such learnt samplers can achieve impressively accurate results on a challenging lattice field theory example.