Kraftons InZoihas gained attention for its detailed graphics and extensive customization options that bring a new level of realism to the life simulation genre. From facial features and clothing to home design and even city editing, players have the freedom to shape their virtual world according to their preferences. In fact, InZoi has a built-in platform called Canvas that lets you share your lot designs with other players and even download their creations to use in your own cities.

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Enter now for the Infosecurity Picks Awards 2025.

Metroid Prime 4: Beyond looks great, but it's Samus's new psychic powers that have me most intrigued.

Law school applications typically spike in times of financial and labor market distress, but a significant recent surge may be more driven by other factors.According to the Law School Admissions Council (LSAC)which, among other things, administers the law school admissions test (LSAT)application volume for the 2025 school year is up 20.5% compared to last year.When we ask test takers and applicants Why are you applying to law school?, the primary reason is to make a difference, says LSACs interim president and CEO Susan Krinsky. As a result, she attributes the latest increase to the world around us, explaining there have been a few very interesting Supreme Court cases, and then weve got the political environment.Krinsky adds that election years often see somewhat higher law school applicant numbers, but such a significant jump is usually only typical in times of severe economic distress, like the 2008 financial crisis or the early pandemic.We will often see at least a small bump in U.S. presidential election years, but not like this one. This one is unique, she says, adding that while financial motivations are likely still a significant motivator they now appear to be secondary.The increase in law school applications also follows a similar spike in business school applications this year, which experts also believe was more divorced from underlying economic conditions than is typical.Like law school hopefuls, many business school applicants said they wanted the degree to make a greater impact, as well as to achieve greater work-life balance, and to guard themselves against the unpredictable effects of artificial intelligence.Competition is heating upNot only is the number of law school applicants up this year, but LSAC data suggests each is also applying to more programs, suggesting significant competition for limited spots.The number of people applying is up about 20%. The [number of] applications theyre submitting, however, is up more like 23%, Krinsky says. I dont think law schools are going to enlarge the size of their classes, given that its very important to law schools that their students get jobs at the other end, and its hard to predict what the market will look like three years from now.According to The Wall Street Journal, the 166 year-old University of Michigan Law School recently reached a new application volume record, while Creighton University School of Law reported a 25% increase. A spokesperson from Columbia Law School also confirmed to Fast Company that their law school, too, has seen an increase in application volume for its incoming cohort.Having done this for a long time, most of these increases and decreases are plus or minus 5%when its a big moment, its maybe 10%, says Georgetown Law School dean of admissions Andy Cornblatt. For it to be up 20% nationally, and 25% at Georgetown, is highly unusual.Prior to the fall of 2021 Cornblatt says no U.S. law school had surpassed about 12,600 applicants in a single academic year. During the pandemic, applications for Georgetowns 650-person law school hit a new record of 14,000 applications, and Cornblatt says this year is on pace to match or surpass that figure.In recessions, applications go up every time. Thats not this, he says. If you go back over time, these presidential election yearsparticularly recentlygenerate an enormous amount of interest in law and politics and policy and the courts; all of those things become front and center.Cornblatt adds that some economic uncertainty, looser policies around entrance exam requirements, and the heightened visibility of legal decisions in the social media age are all contributing factors, but none alone would explain such a significant surge.I tell students the playing field used to be boardroomsthats your grandparents generation, he says. The playing field now is the courtroom, and thats where this new surge of applicants wants to be, because thats where the action is.What an historically competitive year means for applicantsThe significant and widely unexpected increase in interest has forced law schools like Georgetown to take a somewhat different approach to their admissions process this year, Cornblatt says, with significant implications for applicants.People who last year would have been admitted are now probably sitting on a waitlist, and people who would have been wait-listed were probably denied, he explains. The good news is I am being very conservative with the number of people Ive admitted, and as a result, I think we will be much more active on the waiting list than we have been in the past.In other words, being wait-listed in this highly competitive year should be taken as a more encouraging sign than in a typical year.Applicants competing for those limited spots are also encouraged to apply at more schools than they might otherwise, a trend already emerging in the LSAC data.Part of it is having a really high LSAT scoremore competitive than the average of the school, says Claudia Nelson, the director of operations and client relations at higher education admissions consulting firm Admit Advantage. If you want to be seen as a competitive applicant you need to also have really excellent materialspersonal statements, diversity statements, other addendumand apply early.The start of a four-year trend?Though applicants are probably too late to start their application for the 2025 school year, Nelson advises those seeking admissions in future years to get started as soon as essay questions are made public, typically in mid-to-late-summer.After all, if application volume is indeed being driven by political turmoil, Nelson says law school admissions are likely to remain highly competitive in the years ahead.Weve seen a lot of applicants report that they want to go into civil rights and human rightsand I want to say that [the repeal of] Roe v. Wade was probably a big wake-up call for peopleso its about more than just whats happening in the [labor and financial] markets, she says. If all else stays consistent, well probably see an increase throughout this [presidential] administration.

Have you ever wanted to sign up for an online service but you didnt want to provide your real email address as part of the process?Theres a good chance your email address has your actual name in it. Or perhaps you want to avoid the risk of getting spammed. What if youd rather just sign up privately and have a quick no more emails please button?Thats precisely where a reliable email forwarding service can save the day. It empowers you to create a special disguised email address and then use it when signing up with a new app, services, or website.Youll still get any emails sent to the anonymous email address in your normal email inboxbut the service you sign up with wont ever see your real address, and you can turn off the incoming emails whenever you like.Most such services require a payment, and they arent all trustworthy. But Ive got a great exception to recommend.Unearth all sorts of fantastic tech treasures with my free Cool Tools newsletter from The Intelligence. A useful new discovery in your inbox every Wednesday!Protect your privacy with anonymous email addressesThe best email-masking service for casual, everyday purposes is SimpleLogin. Its owned by Protona reputable company with a history of trust around the privacy-focused ProtonMail and ProtonVPN services. With a free SimpleLogin account, you can create up to 10 disguised email aliases for free. You can then use them wherever you want online to shield your real email address. You can get started in about 30 seconds:Go to the SimpleLogin website and sign up for an account. Just provide your real email address (here, at least, lest you be unable to receive any of your fake-address forwarding messages)then choose a password and click a link sent to your real email account to confirm.Click Random Alias on the SimpleLogin dashboard to create your first new random email alias. (There are other options, tooand a nice little tutorial.)Provide that email alias to any website while creating an account instead of your actual, real address.~simplelogin.pngSimpleLogin makes it easy to create and copy privacy-minded masked addresses.~Thats it! You can manage email addresses on the SimpleLogin sitefor example, you can click a switch and stop receiving new emails sent to the alias. Its very helpful for avoiding spam.SimpleLogin is available on the web as well as through an Android app and iPhone app, if youd rather.The service is free for up to 10 aliases. For $36 per year, you can get unlimited aliases and more features, including the premium version of the Proton Pass password manager.SimpleLogins privacy policy looks great. The service says it never keeps your emails, and it does not log your IP address.Treat yourself to even more tech treasures with my free Cool Tools newsletterone new off-the-beaten-path gem in your inbox every Wednesday and an instant introduction to an exceptional audio tool to start!

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Reinforcement Learning from Verifiable Rewards (RLVR) has recently emerged as a promising method for enhancing reasoning abilities in language models without direct supervision. This approach has shown notable success in mathematics and coding, where reasoning naturally aligns with structured problem-solving. While studies have demonstrated that RLVR alone can lead to self-evolved reasoning, research has largely been limited to these technical fields. Efforts to extend RLVR have explored synthetic datasets, such as those involving sequential tasks and object counting, indicating potential but also highlighting the challenges of adapting this method to different domains.Expanding RLVR to broader areas remains an open challenge, particularly in tasks like multiple-choice question answering (MCQA), which provides structured, verifiable labels across diverse subjects, including medicine. However, unlike math and coding, which involve complex reasoning with an open-ended answer space, MCQA tasks typically have predefined answer choices, making it uncertain whether RLVRs benefits translate effectively. This limitation is especially relevant in medical reasoning tasks, where models must navigate intricate clinical knowledge to produce accurate responses, an area that has proven difficult for existing AI systems.Researchers from Microsoft Research investigate whether medical reasoning can emerge through RLVR. They introduce MED-RLVR, leveraging medical MCQA data to assess RLVRs effectiveness in the medical domain. Their findings show that RLVR extends beyond math and coding, achieving performance comparable to supervised fine-tuning (SFT) in in-distribution tasks while significantly improving out-of-distribution generalization by eight percentage points. Analyzing training dynamics, they observe that reasoning capabilities emerge in a 3B-parameter base model without explicit supervision, highlighting RLVRs potential for advancing reasoning in knowledge-intensive fields like medicine.RL optimizes decision-making by training an agent to maximize rewards through interactions with an environment. It has been effectively applied to language models to align outputs with human preferences and, more recently, to elicit reasoning without explicit supervision. This study employs Proximal Policy Optimization (PPO) to train a policy model, incorporating a clipped objective function to stabilize training. Using a rule-based reward function, MED-RLVR assigns rewards based on output correctness and format validity. Without additional supervision, the model demonstrates emergent medical reasoning, similar to mathematical reasoning in prior RLVR studies, highlighting RLVRs potential beyond structured domains.The MedQA-USMLE dataset, which includes multi-choice medical exam questions, is used to train MED-RLVR. Unlike the standard four-option version, this dataset presents a greater challenge by offering more answer choices. Training is based on the Qwen2.5-3B model using OpenRLHF for reinforcement learning. Compared to SFT, MED-RLVR demonstrates superior generalization, particularly on the MMLU-Pro-Health dataset. Analysis reveals six stages of reasoning evolution: format failures, verbose outputs, reward hacking, and reintegrated reasoning. Unlike math or coding tasks, no self-validation behaviors (aha-moments) were observed, suggesting potential improvements through penalizing short reasoning chains or fine-tuning with longer CoTs.In conclusion, the study focuses on MCQA in medicine, providing a controlled setting for evaluation. However, MCQA does not fully capture the complexity of real-world tasks like open-text answering, report generation, or medical dialogues. Additionally, the unimodal approach limits the models ability to integrate multimodal data, which is crucial for diagnostic applications. Future work should address these limitations. MED-RLVR, based on reinforcement learning with verifiable rewards, matches SFT on in-distribution tasks and improves out-of-distribution generalization. While medical reasoning emerges without explicit supervision, challenges like reward hacking persist, highlighting the need for further exploration of complex reasoning and multimodal integration.Check outthe Paper.All credit for this research goes to the researchers of this project. Also,feel free to follow us onTwitterand dont forget to join our85k+ ML SubReddit. Sana HassanSana Hassan, a consulting intern at Marktechpost and dual-degree student at IIT Madras, is passionate about applying technology and AI to address real-world challenges. With a keen interest in solving practical problems, he brings a fresh perspective to the intersection of AI and real-life solutions.Sana Hassanhttps://www.marktechpost.com/author/sana-hassan/Efficient Inference-Time Scaling for Flow Models: Enhancing Sampling Diversity and Compute AllocationSana Hassanhttps://www.marktechpost.com/author/sana-hassan/UCLA Researchers Released OpenVLThinker-7B: A Reinforcement Learning Driven Model for Enhancing Complex Visual Reasoning and Step-by-Step Problem Solving in Multimodal SystemsSana Hassanhttps://www.marktechpost.com/author/sana-hassan/Vision-R1: Redefining Reinforcement Learning for Large Vision-Language ModelsSana Hassanhttps://www.marktechpost.com/author/sana-hassan/Understanding and Mitigating Failure Modes in LLM-Based Multi-Agent Systems