Lipograms are a unique form of constrained writing where all occurrences of a particular letter are excluded from the text, typified by the novel Gadsby, which daringly avoids all usage of the letter 'e'. In this study, we explore the power of modern large language models (LLMs) by transforming the novel F. Scott Fitzgerald's The Great Gatsby into a fully 'e'-less text. We experimented with a range of techniques, from baseline methods like synonym replacement to sophisticated generative models enhanced with beam search and named entity analysis. We show that excluding up to 3.6% of the most common letters (up to the letter 'u') had minimal impact on the text's meaning, although translation fidelity rapidly and predictably decays with stronger lipogram constraints. Our work highlights the surprising flexibility of English under strict constraints, revealing just how adaptable and creative language can be.

In Indiana, Exploration Acres found a way to keep the family farm alive. Exploration Acres has operated its award-winning corn maze for almost 20 years. Breakthroughs, discoveries, and DIY tips sent every weekday. The adage refers to a farmer's goal for their crops if they hope to make the October harvest. And while most Midwesterners are familiar with the axiom, Tim Fitzgerald knows the folksy refrain lost its relevancy decades ago.

Google has been paying Samsung tons of cash every month to pre-install the AI app Gemini on its smartphones, according to a report by Bloomberg . This information comes to us as part of a pre-existing antitrust case against Google. Peter Fitzgerald, Google's VP of platforms and device partnerships, testified in federal court that it began paying Samsung for this service back in January. The pair of companies have a contract that's set to run at least two years. Fitzgerald told Judge Amit Metha, who is overseeing the case, that Google provides Samsung with both fixed monthly payments and a percentage of revenue earned from advertisers within the Gemini app.

The Kessler syndrome refers to the escalating space debris from frequent space activities, threatening future space exploration. Addressing this issue is vital. Several AI models, including Convolutional Neural Networks, Kernel Principal Component Analysis, and Model-Agnostic Meta- Learning have been assessed with various data types. Earlier studies highlighted the combination of the YOLO object detector and a linear Kalman filter (LKF) for object detection and tracking. Advancing this, the current paper introduces a novel methodology for the Comprehensive Orbital Surveillance and Monitoring Of Space by Detecting Satellite Residuals (CosmosDSR) by combining YOLOv3 with an Unscented Kalman Filter (UKF) for tracking satellites in sequential images. Using the Spacecraft Recognition Leveraging Knowledge of Space Environment (SPARK) dataset for training and testing, the YOLOv3 precisely detected and classified all satellite categories (Mean Average Precision=97.18%, F1=0.95) with few errors (TP=4163, FP=209, FN=237). Both CosmosDSR and an implemented LKF used for comparison tracked satellites accurately for a mean squared error (MSE) and root mean squared error (RME) of MSE=2.83/RMSE=1.66 for UKF and MSE=2.84/RMSE=1.66 for LKF. The current study is limited to images generated in a space simulation environment, but the CosmosDSR methodology shows great potential in detecting and tracking satellites, paving the way for solutions to the Kessler syndrome.

This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants$\unicode{x2014}$what we call ''shared intelligence''. This vision is premised on active inference, a formulation of adaptive behavior that can be read as a physics of intelligence, and which inherits from the physics of self-organization. In this context, we understand intelligence as the capacity to accumulate evidence for a generative model of one's sensed world$\unicode{x2014}$also known as self-evidencing. Formally, this corresponds to maximizing (Bayesian) model evidence, via belief updating over several scales: i.e., inference, learning, and model selection. Operationally, this self-evidencing can be realized via (variational) message passing or belief propagation on a factor graph. Crucially, active inference foregrounds an existential imperative of intelligent systems; namely, curiosity or the resolution of uncertainty. This same imperative underwrites belief sharing in ensembles of agents, in which certain aspects (i.e., factors) of each agent's generative world model provide a common ground or frame of reference. Active inference plays a foundational role in this ecology of belief sharing$\unicode{x2014}$leading to a formal account of collective intelligence that rests on shared narratives and goals. We also consider the kinds of communication protocols that must be developed to enable such an ecosystem of intelligences and motivate the development of a shared hyper-spatial modeling language and transaction protocol, as a first$\unicode{x2014}$and key$\unicode{x2014}$step towards such an ecology.

Teenagers deserve to grow, develop, and experiment, says Caitriona Fitzgerald, deputy director at the Electronic Privacy Information Center (EPIC), a nonprofit advocacy group. They should be able to test or abandon ideas "while being free from the chilling effects of being watched or having information from their youth used against them later when they apply to college or apply for a job." She called for the Federal Trade Commission (FTC) to make rules to protect the digital privacy of teens. Hye Jung Han, the author of a Human Rights Watch report about education companies selling personal information to data brokers, wants a ban on personal data-fueled advertising to children. "Commercial interests and surveillance should never override a child's best interests or their fundamental rights, because children are priceless, not products," she said.

The Middleby Corporation announced the acquisition of Proxaut, a leading manufacturer of Auto Guided Vehicles (AGVs) for the food industry and industrial processing companies. The company is based in Italy near Bologna with approximately $15 million USD in annual sales. "We are leading the trend for Industry 4.0 in food processing. Our recent strategic investments in automation are coming to fruition, as we see order demands for this technology" Proxaut AGV technology is used by industry leading manufacturers in a variety of capacities, primarily to move materials and products safely and operate alongside people. Proxaut automation decreases repetitive movements from traditional labor and ergonomically improves workflows.

We address two domains of skill transfer problems encountered by an autonomous robot: within-domain adaptation and cross-domain transfer. Our aim is to provide skill representations which enable transfer in each problem classification. As such, we explore two approaches to skill representation which address each problem classification separately. The first representation, based on mimicking, encodes the full demonstration and is well suited for within-domain adaptation. The second representation is based on imitation and serves to encode a set of key points along the trajectory, which represent the goal points most relevant to the successful completion of the skill. This representation enables both within-domain and cross-domain transfer. A planner is then applied to these constraints, generating a domain-specific trajectory which addresses the transfer task.

Facebook announced last year that it was committed to putting $10 billion into the virtual world: its metaverse division. And last week, news broke that Microsoft was nearing a $70 billion deal to buy Activision Blizzard, the video game publisher of World of Warcraft and other top-selling games. As Microsoft's biggest entry into gaming, the deal indicates the company is betting big on the growth of the virtual space, as it works to compete with tech rivals like Facebook. It's clear that the metaverse -- a new virtual reality sector that reimagines the internet as a 3D experience that users can be a part of -- is being hyped by tech titans as the future of the internet, but what does it mean for the future of healthcare? The COVID-19 pandemic ushered in a new healthcare consumer conditioned to home delivery of medicines and receiving healthcare online through telehealth visits (including Medicare recipients).

Covid-19 has focused businesses more and more on their supply chains, said fast-emerging Cork business Kwayga's CEO Martin Fitzgerald. "Right now, businesses are seeking new solutions to help buyers diversify their suppliers, and suppliers to diversify their markets." Kwayga is a B2B matching platform for buyers and suppliers in the food sector designed around trust and security. Using the platform buyers and suppliers discover, verify, match, connect, communicate in any language and trade. "Kwayga focuses on democratising international trade for mid-sized businesses by putting the right buyers with the right suppliers at the right time. Trust is the key component. We use AI to verify company profiles, we protect buyers from unsolicited approaches by giving them strong privacy controls, and we make a promise to suppliers that the deals posted on our platform are from real verified buyers."