Tottenham may have coasted through to the Champions League last 16, but their Premier League form remains a problem for boss Thomas Frank. I was at their draw with Burnley last week and there are a lot of angry Spurs fans out there, said BBC Sport football expert Chris Sutton. Their domestic results are such a contrast to their record in Europe, and it could be another difficult afternoon for Frank when they face Manchester City on Sunday. Sutton is making predictions for all 380 Premier League games this season, against AI, BBC Sport readers and a variety of guests. His guest for week 24 is boxer Francesca Hennessy, who supports Chelsea . Hennessy faces Ellie Bouttell in a WBC title eliminator on Saturday, live on BBC Two from 20:00 GMT.

Is this AI's worst prediction yet? Chris Sutton's guest this week, actor Éanna Hardwicke, plays Roy Keane in Saipan - a new film about the former Manchester United captain's infamous fallout with Republic of Ireland manager Mick McCarthy before the 2002 World Cup. It is in cinemas from Friday. Naturally, we asked AI who would play Sutton if a film were ever made about him. The best fit, apparently, is Hollywood heartthrob Tom Hardy - who is four inches shorter than BBC Sport football expert Sutton but is AI's top choice for the role because he is known for portraying tough, brooding characters with emotional depth. That just shows how way off the mark AI is, said Sutton. But I'm happy with Tom Hardy, even though he is not tall enough.

Data duplication within large-scale corpora often impedes large language models' (LLMs) performance and privacy. In privacy-concerned federated learning scenarios, conventional deduplication methods typically rely on trusted third parties to perform uniform deletion, risking loss of informative samples while introducing privacy vulnerabilities. To address these gaps, we propose Federated ReWeighting (FedRW), the first privacy-preserving framework, to the best of our knowledge, that performs soft deduplication via sample reweighting instead of deletion in federated LLM training, without assuming a trusted third party. At its core, FedRW proposes a secure, frequency-aware reweighting protocol through secure multi-party computation, coupled with a parallel orchestration strategy to ensure efficiency and scalability. During training, FedRW utilizes an adaptive reweighting mechanism with global sample frequencies to adjust individual loss contributions, effectively improving generalization and robustness. Empirical results demonstrate that FedRW outperforms the state-of-the-art method by achieving up to 28.78x speedup in preprocessing and approximately 11.42% improvement in perplexity, while offering enhanced security guarantees. FedRW thus establishes a new paradigm for managing duplication in federated LLM training.

From sugar shortages to military contracts, World War II helped make M&Ms and Hershey's bars into symbols of American abundance. A 1940s Milky Way ad shows candy keeping pilots smiling through the war. Breakthroughs, discoveries, and DIY tips sent every weekday. Every year, Hershey manufactures 373 million of its signature milk chocolate bars . While the company doesn't release exact stats on Halloween sales, you can bet a lot of those end up in plastic Jack O'Lantern-shaped pails.

Devindra: because like you could just always just take a photo of something and be like, yeah, that's how we wonder if it's going to Cherlynn: be a ram hog.

We employ Large language models (LLMs) such as GPT-fine-tuning on the LLaMa-2, Mixtral 8 7B, 4 (OpenAI, 2023), BLOOM (Le Scao et al, Gemma, and conduct a comprehensive evaluation 2023), LLaMa-2 (Touvron et al, 2023), Mistral of Vietnamese LLMs across various scenarios and (Jiang et al., 2023), Mixtral (Jiang et al., 2024), settings. Throughout the thorough evaluation process, Gemma (Team et al., 2024) have made significant we observe the following: (i) larger language contributions to the field of natural language processing models exhibit unseen capabilities compared to (NLP). Despite their advancements, a gap smaller counterparts; (ii) larger language models remains in their specialization for many languages, tend to manifest more biases, produce uncalibrated including Vietnamese. This paper addresses the results, and are more susceptible to the influence development and evaluation of Vietnamese-centric of input prompts; (iii) the quality of training or LLMs. Vietnam, with a population surpassing 100 fine-tuning datasets is the key for unlocking LLM million, ranks as the 16th most populous country performance. Our key contributions include: globally.

ShareThis week, we will briefly touch upon the topic of artificial intelligence, or AI, discuss what it is, why it is so important to the American empire and national security, and how the ancient Chamorro people of the Marianas can prepare themselves to be ready for future possible job and entrepreneurial opportunities at the intersection of warfare and technology.  What is AI? Star Wars gone wild?  AI is a constellation or universe of technologies, computer hardware and software, designed to solve specific tasks that reflect and are intended to resemble human cognitive processes to include decision making, reasoning, learning, and perceiving.  AI has applications that reprogram itself to complete specific tasks called machine learning. Within the machine learning space, there are applications that take information to produce outcomes with increasing accuracy. This technology can be interpreted as an evolving manufactured ecosystem that attempts to some degree to self-develop and monitor without human intervention.  This is both potentially dangerous and beneficial stuff.  Why AI is important to the United States and our ancient Chamorro people Part of the answer is found in a report released by the congressionally established National Security Commission on Artificial Intelligence, which outlined the national importance of AI and its application to all facets of American—and by implication, American colonial—society. The commission was established to assess how AI affects imperial competitiveness and technological advantage.  AI is important because it has civilian and military applications that are used every day by every citizen, whether one resides on Saipan, Rota, in New York, Birmingham or elsewhere. If you are looking for a movie to watch or check out what time a restaurant or bar opens, or get vehicle maintenance service, or asking your iPhone a question, AI will be a part of the enabling infrastructure that will get you the answers to your questions.  AI is now found everywhere and is used knowingly or unknowingly, again posing benefits and concerns to society.  If Guam moves toward building a new hospital, AI will be an integral and ubiquitous part of how healthcare decisions are informed, how biotechnology is implemented, and how personal medical information and data are managed, distributed, protected, and delivered. AI will become more important as Guam continues to move toward technological solutions for future energy, food technology and security opportunities. Folks in the NMI will see a greater role of AI as the Commonwealth moves toward electric and eventually unmanned cars. Cyber-attacks against the United States government and other facets of society occur every day. AI was the underbelly used to enable computer networks to find vulnerabilities recently when the government of Guam experienced a cyber-attack. These attacks may come in the form of data harvesting, targeted attacks on individual citizens, or AI enabled attacks on social media, intended to influence or harm the targets.   The American national government is contemplating ways to aggressively deal with data protection, privacy, and security. Congress remains behind the curve on how to craft legislation to address ongoing technological change. Others worry that domestic data surveillance is out of control and has already compromised our privacy and protection.  Why AI is important to the governments of Guam and the CNMI Now is the time for the governments of Guam and the CNMI to consider creating a Marianas Artificial Intelligence, Security and Emerging Technologies Understanding advisory board to learn and more completely seek to comprehend the nature of AI, how it is currently used and how it presents opportunities and vulnerabilities to every aspect of Pacific island life. There is no reason why Guam and CNMI legislative committees overseeing technology cannot hold initial hearings to discuss AI.  Future educational and career opportunities: Pay attention Guam Community College is doing some work with its resources available to students in math and science tutoring and management information systems programming. The University of Guam has resources that can or will eventually be able to contribute toward providing AI jobs for young islanders who have math, engineering, nursing, education, biology, and Chamorro studies backgrounds.  Guam institutions have opportunities to further partner with the Guam Department of Education, and the CNMI Public School System on the implications of AI. Marianas educational institutions would be well served to contemplate the establishment of emerging technology certificate programs to prepare Pacific Islanders for much needed and well-paid technology jobs. All Marianas institutions can also create opportunities to seek partnerships with major American companies and entities in Silicon Valley and elsewhere, intended to create AI related jobs and training.  Lawmakers from Guam and the CNMI as well as the governors can contemplate creating national level digital annex risk management programs for all school age kids interested in future technical challenges that will provide good paying jobs while helping to secure America and its colonies. Science and technology partnerships with Taiwan and South Korea may also be something that can be operationalized for mutual benefit.  The AI race is on, security threats increase A most dangerous aspect of rapidly emerging AI enabled technology and networks is that nation state adversaries such as China and Russia may outpace the United States on this front over the next 10 to 15 years. This presents and will present fundamental risks and threats to the existing militarized resource base currently embedded and/or connected to Guam and the CNMI that may include risks tied to autonomous unmanned weapon system warfare and real future risks associated with crisis stability and human authorized employment of very dangerous nuclear weapons and networks through unmanned platforms.  AI threatens to pose real challenges to traditional process identification and validation issues related to military targeting matters, creating risks to real-time battle assessment decisions that will need to be made in the future.   Now is the time for our Chamorro Pacific Islander civilization to continue the broad conversation on issues of the military and national and colonial security to demystify and assess the importance of AI and what it means to all our families and friends in the 21st century. 

Multi-hop Reading Comprehension (RC) requires reasoning and aggregation across several paragraphs. We propose a system for multi-hop RC that decomposes a compositional question into simpler sub-questions that can be answered by off-the-shelf single-hop RC models. Since annotations for such decomposition are expensive, we recast sub-question generation as a span prediction problem and show that our method, trained using only 400 labeled examples, generates sub-questions that are as effective as human-authored sub-questions. We also introduce a new global rescoring approach that considers each decomposition (i.e. the sub-questions and their answers) to select the best final answer, greatly improving overall performance. Our experiments on HotpotQA show that this approach achieves the state-of-the-art results, while providing explainable evidence for its decision making in the form of sub-questions.

This article describes a Turing machine which can solve for $\beta^{'}$ which is RE-complete. RE-complete problems are proven to be undecidable by Turing's accepted proof on the Entscheidungsproblem. Thus, constructing a machine which decides over $\beta^{'}$ implies inconsistency in ZFC. We then discover that unrestricted use of the axiom of substitution can lead to hidden assumptions in a certain class of proofs by contradiction. These hidden assumptions create an implied axiom of incompleteness for ZFC. Later, we offer a restriction on the axiom of substitution by introducing a new axiom which prevents impredicative tautologies from producing theorems. Our discovery in regards to these foundational arguments, disproves the SPACE hierarchy theorem which allows us to solve the P vs NP problem using a TIME-SPACE equivalence oracle.