June 7 Monument of Branimir 879 – Pope John VIII officially recognised Croatia as an independent state, and Branimir (monument pictured) as its duke. 1628 – The Petition of Right, a major English constitutional document that set out specific liberties of individuals, received royal assent from King Charles I. 1917 – First World War: The British Army detonated 19 ammonal mines under German lines, killing perhaps 10,000 in the deadliest non-nuclear man-made explosion in history during the Battle of Messines. 1948 – Anti-Jewish riots broke out in the French protectorate in Morocco, during which 44 people were killed and 150 injured. 1969 – In their only UK concert, the rock supergroup Blind Faith, featuring Eric Clapton, Steve Winwood and Ginger Baker, debuted in London's Hyde Park in front of 100,000 fans. Roderigo Lopes (d. 1594)Paul Gauguin (b. 1848)Louise Erdrich (b. 1954)Mike Pence (b. 1959) More anniversaries: June 6 June 7 June 8 Archive By email List of days of the year About

June 4: Trianon Treaty Day in Romania (1920) German submarine U-505 1784 – Élisabeth Thible became the first woman to fly in an untethered hot air balloon, covering a distance of 4 km (2.5 mi) and reaching an estimated altitude of 1,500 m (4,900 ft). 1944 – World War II: A United States Navy task group captured German submarine U-505 (pictured). 1974 – Major League Baseball's Cleveland Indians hosted Ten Cent Beer Night, but had to forfeit the game to the Texas Rangers due to rioting by drunken fans. 1989 – Following the death of Ruhollah Khomeini, the Assembly of Experts elected Ali Khamenei to be Supreme Leader of Iran. Antoine, Duke of Lorraine (b. 1489)Benjamin Huntsman (b. 1704)Miguel de Azcuénaga (b. 1754)Chester Nez (d. 2014) More anniversaries: June 3 June 4 June 5 Archive By email List of days of the year About

Modern software engineering faces growing challenges in accurately retrieving and understanding code across diverse programming languages and large-scale codebases. Existing embedding models often struggle to capture the deep semantics of code, resulting in poor performance in tasks such as code search, RAG, and semantic analysis. These limitations hinder developers’ ability to efficiently locate relevant code snippets, reuse components, and manage large projects effectively. As software systems grow increasingly complex, there is a pressing need for more effective, language-agnostic representations of code that can power reliable and high-quality retrieval and reasoning across a wide range of development tasks.  Mistral AI has introduced Codestral Embed, a specialized embedding model built specifically for code-related tasks. Designed to handle real-world code more effectively than existing solutions, it enables powerful retrieval capabilities across large codebases. What sets it apart is its flexibility—users can adjust embedding dimensions and precision levels to balance performance with storage efficiency. Even at lower dimensions, such as 256 with int8 precision, Codestral Embed reportedly surpasses top models from competitors like OpenAI, Cohere, and Voyage, offering high retrieval quality at a reduced storage cost. Beyond basic retrieval, Codestral Embed supports a wide range of developer-focused applications. These include code completion, explanation, editing, semantic search, and duplicate detection. The model can also help organize and analyze repositories by clustering code based on functionality or structure, eliminating the need for manual supervision. This makes it particularly useful for tasks like understanding architectural patterns, categorizing code, or supporting automated documentation, ultimately helping developers work more efficiently with large and complex codebases.  Codestral Embed is tailored for understanding and retrieving code efficiently, especially in large-scale development environments. It powers retrieval-augmented generation by quickly fetching relevant context for tasks like code completion, editing, and explanation—ideal for use in coding assistants and agent-based tools. Developers can also perform semantic code searches using natural language or code queries to find relevant snippets. Its ability to detect similar or duplicated code helps with reuse, policy enforcement, and cleaning up redundancy. Additionally, it can cluster code by functionality or structure, making it useful for repository analysis, spotting architectural patterns, and enhancing documentation workflows.  Codestral Embed is a specialized embedding model designed to enhance code retrieval and semantic analysis tasks. It surpasses existing models, such as OpenAI’s and Cohere’s, in benchmarks like SWE-Bench Lite and CodeSearchNet. The model offers customizable embedding dimensions and precision levels, allowing users to effectively balance performance and storage needs. Key applications include retrieval-augmented generation, semantic code search, duplicate detection, and code clustering. Available via API at $0.15 per million tokens, with a 50% discount for batch processing, Codestral Embed supports various output formats and dimensions, catering to diverse development workflows. In conclusion, Codestral Embed offers customizable embedding dimensions and precisions, enabling developers to strike a balance between performance and storage efficiency. Benchmark evaluations indicate that Codestral Embed surpasses existing models like OpenAI’s and Cohere’s in various code-related tasks, including retrieval-augmented generation and semantic code search. Its applications span from identifying duplicate code segments to facilitating semantic clustering for code analytics. Available through Mistral’s API, Codestral Embed provides a flexible and efficient solution for developers seeking advanced code understanding capabilities.  vides valuable insights for the community. Check out the Technical details. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 95k+ ML SubReddit and Subscribe to our Newsletter. 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/Off-Policy Reinforcement Learning RL with KL Divergence Yields Superior Reasoning in Large Language ModelsSana Hassanhttps://www.marktechpost.com/author/sana-hassan/This AI Paper from Microsoft Introduces WINA: A Training-Free Sparse Activation Framework for Efficient Large Language Model InferenceSana Hassanhttps://www.marktechpost.com/author/sana-hassan/Apple and Duke Researchers Present a Reinforcement Learning Approach That Enables LLMs to Provide Intermediate Answers, Enhancing Speed and AccuracySana Hassanhttps://www.marktechpost.com/author/sana-hassan/National University of Singapore Researchers Introduce Dimple: A Discrete Diffusion Multimodal Language Model for Efficient and Controllable Text Generation

June 3: Martyrs Day in Uganda Silhouette of Jack Jouett 1781 – American Revolutionary War: Jack Jouett (pictured) rode 40 miles (64 km) to warn Thomas Jefferson and the Virginia legislature of British cavalry who had been sent to capture them. 1892 – Liverpool F.C., one of England's most successful football clubs, was founded. 1937 – Half a year after abdicating the British throne, Edward, Duke of Windsor, married American socialite Wallis Simpson in a private ceremony in France. 1969 – During a SEATO exercise in the South China Sea, a collision between HMAS Melbourne and USS Frank E. Evans resulted in the latter vessel being cut in two and the deaths of 74 personnel. 1982 – A failed assassination attempt was made on Shlomo Argov, the Israeli ambassador to the United Kingdom, triggering an Israeli decision to invade Lebanon three days later. Garret Hobart (b. 1844)Eric A. Havelock (b. 1903)Franz Kafka (d. 1924)Pierre Poilievre (b. 1979) More anniversaries: June 2 June 3 June 4 Archive By email List of days of the year About

In the summer of 2023, I wrote about a shocking scandal at Harvard Business School: Star professor Francesca Gino had been accused of falsifying data in four of her published papers, with whispers there was falsification in others, too. A series of posts on Data Colada, a blog that focuses on research integrity, documented Gino’s apparent brazen data manipulation, which involved clearly changing study data to better support her hypotheses. This was a major accusation against a researcher at the top of her field, but Gino’s denials were unconvincing. She didn’t have a good explanation for what had gone wrong, asserting that maybe a research assistant had done it, even though she was the only author listed across all four of the falsified studies. Harvard put her on unpaid administrative leave and barred her from campus.The cherry on top? Gino’s main academic area of study was honesty in business.As I wrote at the time, my read of the evidence was that Gino had most likely committed fraud. That impression was only reinforced by her subsequent lawsuit against Harvard and the Data Colada authors. Gino complained that she’d been defamed and that Harvard hadn’t followed the right investigation process, but she didn’t offer any convincing explanation of how she’d ended up putting her name to paper after paper with fake data.This week, almost two years after the news first broke, the process has reached its resolution: Gino was stripped of tenure, the first time Harvard has essentially fired a tenured professor in at least 80 years. (Her defamation lawsuit against the bloggers who found the data manipulation was dismissed last year.)What we do right and wrong when it comes to scientific fraudHarvard is in the news right now for its war with the Trump administration, which has sent a series of escalating demands to the university, canceled billions of dollars in federal grants and contracts, and is now blocking the university from enrolling international students, all in an apparent attempt to force the university to conform to MAGA’s ideological demands. Stripping a celebrity professor of tenure might not seem like the best look at a moment when Harvard is in an existential struggle for its right to exist as an independent academic institution. But the Gino situation, which long predates the conflict with Trump, shouldn’t be interpreted solely through the lens of that fight. Scientific fraud is a real problem, one that is chillingly common across academia. But far from putting the university in a bad light, Harvard’s handling of the Gino case has actually been unusually good, even though it still underscores just how much further academia has to go to ensure scientific fraud becomes rare and is reliably caught and punished.There are two parts to fraud response: catching it and punishing it. Academia clearly isn’t very good at the first part. The peer-review process that all meaningful research undergoes tends to start from the default assumption that data in a reviewed paper is real, and instead focuses on whether the paper represents a meaningful advance and is correctly positioned with respect to other research. Almost no reviewer is going back to check to see if what is described in a paper actually happened.Fraud, therefore, is often caught only when other researchers actively try to replicate a result or take a close look at the data. Science watchdogs who find these fraud cases tell me that we need a strong expectation that data be made public — which makes it much harder to fake — as well as a scientific culture that embraces replications. (Given the premiums journals put on novelty in research and the supreme importance of publishing for academic careers, there’s been little motivation for scientists to pursue replication.). It is these watchdogs, not anyone at Harvard or in the peer-review process, who caught the discrepancies that ultimately sunk Gino.Crime and no punishmentEven when fraud is caught, academia too often fails to properly punish it. When third-party investigators bring a concern to the attention of a university, it’s been unusual for the responsible party to actually face consequences. One of Gino’s co-authors on one of the retracted papers was Dan Ariely, a star professor of psychology and behavioral economics at Duke University. He, too, has been credibly accused of falsifying data: For example, he published one study that he claimed took place at UCLA with the assistance of researcher Aimee Drolet Rossi. But UCLA says the study didn’t happen there, and Rossi says she did not participate in it. In a past case, he claimed on a podcast to have gotten data from the insurance company Delta Dental, which the company says it did not collect. In another case, an investigation by Duke reportedly found that data from a paper he co-authored with Gino had been falsified, but that there was no evidence Ariely had used fake data knowingly.Frankly, I don’t buy this. Maybe an unlucky professor might once end up using data that was faked without their knowledge. But if it happens again, I’m not willing to credit bad luck, and at some point, a professor who keeps “accidentally” using falsified or nonexistent data should be out of a job even if we can’t prove it was no accident. But Ariely, who has maintained his innocence, is still at Duke. Or take Olivier Voinnet, a plant biologist who had multiple papers conclusively demonstrated to contain image manipulation. He was found guilty of misconduct and suspended for two years. It’s hard to imagine a higher scientific sin than faking and manipulating data. If you can’t lose your job for that, the message to young scientists is inevitably that fraud isn’t really that serious. What it means to take fraud seriouslyGino’s loss of tenure, which is one of a few recent cases where misconduct has had major career consequences, might be a sign that the tides are changing. In 2023, around when the Gino scandal broke, Stanford’s then-president Marc Tessier-Lavigne stepped down after 12 papers he authored were found to contain manipulated data. A few weeks ago, MIT announced a data falsification scandal with a terse announcement that the university no longer had confidence in a widely distributed paper “by a former second-year PhD student.” It’s reasonable to assume the student was expelled from the program.I hope that these high-profile cases are a sign we are moving in the right direction on scientific fraud because its persistence is enormously damaging to science. Other researchers waste time and energy following false lines of research substantiated by fake data; in medicine, falsification can outright kill people. But even more than that, research fraud damages the reputation of science at exactly the moment when it is most under attack.We should tighten standards to make fraud much harder to commit in the first place, and when it is identified, the consequences should be immediate and serious. Let’s hope Harvard sets a trend.A version of this story originally appeared in the Future Perfect newsletter. 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Long CoT reasoning improves large language models’ performance on complex tasks but comes with drawbacks. The typical “think-then-answer” method slows down response times, disrupting real-time interactions like those in chatbots. It also risks inaccuracies, as errors in earlier reasoning steps can lead to a misleading final answer. Unlike humans, who often share partial thoughts or conclusions during conversations, LLMs delay responses until all reasoning is complete. While RL is commonly used to train reasoning models, it mainly rewards final answers, overlooking useful intermediate insights. There is growing interest in teaching models that alternate between thinking and answering, but this remains a challenge.  RL has become a popular method to enhance reasoning in LLMs, building on its success in aligning models with human preferences. Two common reward types guide RL: outcome-based rewards (ORM), which focus on the final answer, and process-based rewards (PRM), which provide feedback on intermediate reasoning steps. While PRMs offer more detailed supervision, they often rely on human annotation and additional models, making them complex and prone to issues like reward hacking. Separately, efforts to improve LLM reasoning have explored prompting strategies, structured reasoning, tool integration, and methods to reduce latency and improve efficiency.  Researchers from Apple and Duke University introduce Interleaved Reasoning, a new RL approach that enables language models to alternate between thinking and answering when solving complex, multi-step questions. Instead of waiting until the end to respond, models provide informative intermediate answers, which improves feedback for users and guides their reasoning. Using a straightforward rule-based reward, the model is trained to produce helpful reasoning steps, leading to over 80% faster responses and up to 19.3% better accuracy. Trained only on QA and logic datasets, the method demonstrates strong generalization to more challenging benchmarks, such as MATH, GPQA, and MMLU.  The study proposes a reinforcement learning framework to train LLMs for Interleaved Reasoning, where models alternate between internal thinking and user-facing intermediate answers. Each intermediate step, or “sub-answer,” is shared once the model reaches a meaningful milestone in reasoning. A specialized training template with <think> and <answer> tags is used. The approach utilizes rule-based rewards—specifically, format, final accuracy, and conditional intermediate accuracy—to guide learning. Notably, intermediate rewards are applied only when specific criteria are met, ensuring the model prioritizes overall correctness. They also test different reward schemes, such as all-or-none, partial credit, and time-discounted rewards, to optimize the quality of reasoning.  The interleaved reasoning approach was evaluated on both familiar and unfamiliar datasets using Qwen2.5 models (1.5B and 7B). Unlike traditional methods that separate thinking and answering, the interleaved method provides answers incrementally, improving both speed and usefulness. When combined with intermediate rewards, it significantly enhances model performance while reducing response delays by over 80%. Even without exposure to new domains during training, the model adapts well, showing strong generalization. These results highlight the value of interleaved reasoning in making AI systems more responsive and effective in real-world, multi-step reasoning tasks.  In conclusion, the study explores how interleaved reasoning—where models alternate between reasoning and generating intermediate answers—can significantly improve performance and responsiveness. Using the Qwen2.5-1.5B model, the authors show that providing timely intermediate feedback during training boosts accuracy and accelerates response generation. Different RL strategies were tested, with PPO showing stable results, and conditional, time-discounted rewards proving to be the most effective. The method scales well to complex tasks and outperforms traditional think-then-answer baselines. Unlike token-level reward models, this approach employs simple rule-based rewards after completing full reasoning steps, thereby avoiding reward hacking. Ultimately, interleaved reasoning enhances reasoning quality and efficiency without relying on external tools.  Check out the Paper. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 95k+ ML SubReddit and Subscribe to our Newsletter. 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/National University of Singapore Researchers Introduce Dimple: A Discrete Diffusion Multimodal Language Model for Efficient and Controllable Text GenerationSana Hassanhttps://www.marktechpost.com/author/sana-hassan/LLMs Can Now Reason Beyond Language: Researchers Introduce Soft Thinking to Replace Discrete Tokens with Continuous Concept EmbeddingsSana Hassanhttps://www.marktechpost.com/author/sana-hassan/Researchers at UT Austin Introduce Panda: A Foundation Model for Nonlinear Dynamics Pretrained on 20,000 Chaotic ODE Discovered via Evolutionary SearchSana Hassanhttps://www.marktechpost.com/author/sana-hassan/Microsoft Releases NLWeb: An Open Project that Allows Developers to Easily Turn Any Website into an AI-Powered App with Natural Language Interfaces

In early 2004, after defeating Krona, the Justice League and the Avengers said their goodbyes as each team returned to their proper universe. It was the last time that Marvel and DC would cross paths in any official capacity for decades. Well, unless you count the roundabout way of having them duke it out with Fortnite skins. In terms of comics, the two industry giants would keep separate, especially once Marvel was scooped up by Disney. After 21 years, the two worlds will collide once again. In September, Marvel is releasing Deadpool/Batman, written by Zeb Wells with art by Greg Capullo (including backup stories featuring talent like Kevin Smith, Chip Zdarsky, Adam Kubert, and more). Then in November, DC is doing Batman/Deadpool, written by Grant Morrison with art by Dan Mora. On top of that, this is apparently only the beginning, as there will be Marvel/DC crossovers happening on an annual basis. That does bring into question some choice narration from Doctor Manhattan in 2017’s Doomsday Clock. In the DC Universe/Watchmen event, the omnipotent, blue-donged god noted that in 2030 there would be an event known as “The Secret Crisis,” which would involve Superman fighting Thor across the universe and the heroic sacrifice of one unnamed green behemoth. A hopeful joke or something more? Regardless of what the future brings, starting things off with dual meetings between the Dark Knight and the Merc with a Mouth is a brilliant choice. They could have had Superman team up with Spider-Man all over again or something just as on the nose, but this is fresh and has tons of potential. Here are some reasons why. Deadpool Missed Out The first crossover between the companies was 1976’s Superman vs. The Amazing Spider-Man. While there had been a few other attempts in the ‘70s and ‘80s, it wasn’t until the mid-’90s that they went absolutely ham with it. Over a six-year stretch starting in 1994, there were fifteen different team-ups and cross-company battles. This includes the memorable and oh-so-dated Marvel vs. DC event and its dip into Amalgam, the merged reality where Dark Claw (Wolverine/Batman) and his sidekick Sparrow (Jubilee/Robin) fight Hyena (Sabretooth/Joker). Meanwhile, though Deadpool was introduced in 1990, he wasn’t really cared about among comic fans until the 1997 solo run by Joe Kelly and Ed McGuinness. By the time Deadpool really picked up steam in popularity (Deadpool actually won a fight based on reader votes against Daredevil in 1999’s Contest of Champions II), the DC alliance was on its way out. The poor guy didn’t even get to be in Amalgam. They merged Deathstroke the Terminator with Daredevil instead. Centering this Batman story on a mainstream hero who wasn’t mainstream enough back in the ‘90s only adds a new coat of paint onto this novelty. The Previous Batman and Deadpool Crossover Then again, this wouldn’t exactly be the first time Batman and Deadpool have crossed paths. In an unofficial way, they have met. Sort of. As mentioned, the Kelly/McGuinness run of Deadpool was iconic and character-defining. That same creative team worked on Superman/Batman Annual #1 back in 2006. In a modern retelling of the pre-Crisis storyline where Bruce and Clark discovered each other’s secret identities on a cruise, the two had to deal with both Deathstroke and Deathstroke’s heroic Earth-3 doppelganger. Outside of the blue and orange color scheme, Earth-3 Deathstroke was Deadpool in as many ways as they could legally get away with. This included constantly getting interrupted with extreme violence whenever he was about to say his actual name. Still, even being in a separate company never stopped Deadpool from razzing on Batman. In his movies alone, he’s made fun of how dark the DC Universe is, crapped on the ending of Batman v Superman: Dawn of Justice, and joked about how Wolverine’s mask is like Batman’s with actual neck mobility. Speaking of… The Writers Understand the Assignment Zeb Wells might not be the most popular comic writer right now due to reasons involving Ms. Marvel’s death and… Paul. Still, he was one of the writers of Deadpool & Wolverine. People seemed to like that one. The guy knows a thing or two about putting Deadpool with a gruff, brooding superhero with reluctant father issues. This one will probably have less mutual bludgeoning… er, at least I hope it will. Join our mailing list Get the best of Den of Geek delivered right to your inbox! On the other side of things, we have Grant Morrison. Morrison is no stranger to the X-Men corner of Marvel, but he’s strangely never touched Deadpool before. Considering how much Morrison loves playing with the fourth wall and the boundaries between reality and fiction (Animal Man, Flex Mentallo, Seven Soldiers: Zatanna), it’s a real surprise that they never got to write for Marvel’s most self-aware antihero. Letting Deadpool Loose in Gotham On paper, the idea of having Deadpool specifically mixing things up with Harley Quinn might have made for a more fitting crossover. Unfortunately, DC kind of beat that into the ground with their “we can rip off your guy more blatantly than you can rip off ours” creation Red Tool, a regular in Harley’s comics. Regardless, having Deadpool mix it up with the worst of Gotham has legs. If anything, the very idea of Deadpool antagonizing the Joker is enough to sell issues. We could see him make Bane look nearly useless by recovering from a broken spine in seconds. We could find out what happens when Wade huffs fear gas. He could brutalize a confused Penguin for what happened to Victor in the HBO Max season finale. An official Deadpool vs. Deathstroke showdown is on the table. The possibilities are endless! As for Batman, he could… um… He… could fight… huh. Is T-Ray still a thing? Deadpool/Batman #1 will be released on September 17, 2025. Batman/Deadpool #1 is set to arrive in November.

The Days of Play celebration comes to PlayStation Store, featuring numerous games all available at discount for a limited time*, starting May 28! You can get a preview of just some of the titles** that’ll be included ahead of the promotion’s go-live time right here. The full list will include the likes of Call of Duty: Black Ops 6 – Cross-Gen Bundle (45% off), WWE 2K25 Standard Edition (30% off), Astro Bot (15% off), The Last of Us Part II Remastered (20% off) and Red Dead Redemption 2 (75% off).  The full list will include the likes of Call of Duty: Black Ops 6 – Cross-Gen Bundle (45% off), WWE 2K25 Standard Edition (30% off), Astro Bot (17% off) and The Last of Us Part II Remastered (20% off).  The full list will include the likes of Call of Duty: Black Ops 6 – Cross-Gen Bundle (45% off), WWE 2K25 Standard Edition (30% off), Astro Bot (17% off) and The Last of Us Part II Remastered (20% off).  And there are many more games beyond the titles listed below. When the dedicated promotion page goes live on PlayStation Store on May 28, head there to see the full list and find out your regional discount pricing.  And there’s plenty more Days of Play related-celebrations to enjoy! Check out the full range of activities, offers and more in the Days of Play announcement post.  A Plague Tale: Innocence A Plague Tale: Requiem After the Fall® – Complete Edition Agatha Christie – Murder on the Orient Express Age of Mythology: Retold Standard Edition Age of Wonders 4 AI LIMIT AI LIMIT Deluxe Edition AI: THE SOMNIUM FILES AI: THE SOMNIUM FILES – nirvanA Initiative Airport Police Contraband Simulator – Border Patrol Akimbot Alan Wake 2 Deluxe Edition Alan Wake Remastered Alien: Isolation – THE COLLECTION Alien: Rogue Incursion VR Deluxe Ambulance Life: A Paramedic Simulator Amerzone – The Explorer’s Legacy ANIMAL WELL Another Crab’s Treasure Arcade Paradise Arizona Sunshine® 2 Deluxe Edition Arizona Sunshine® Remake Arma Reforger Assassin’s Creed Valhalla Deluxe Assassin’s Creed Valhalla Ragnarök Edition Assassin’s Creed® IV Black Flag™ Assassin’s Creed® Mirage Deluxe Edition Assassin’s Creed® Odyssey Deluxe Edition Assassin’s Creed® Odyssey Gold Edition Assetto Corsa 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After eight seasons and over 200 guest stars, the adult animated franchise "Big Mouth" premiered its final season on Friday.Though it never reached the viewership numbers of behemoths like "Bridgerton" or "Stranger Things," it's one of the streamer's longest running original scripted shows.Across eight years, the series has won five Emmys and inspired the 2022 spin-off, "Human Resources." Season eight concludes the series, which was created by Nick Kroll, his childhood best friend Andrew Goldberg, Jennifer Flackett, and Mark Levin.The season follows a group of teens entering Bridgeton High School and having to rediscover their identities in the new school.As with previous seasons, the teens' hormones, feelings, and mental illnesses are personified through various creatures that appear to help guide the teens through the ups and downs of puberty. Nick Kroll plays Nick and Maury. Nick Kroll plays numerous characters in "Big Mouth." Courtesy of Netflix / Charley Gallay / Getty Images for Netflix Kroll played several human characters, including Nick Birch, the series' lead character, who was inspired by Kroll's childhood.Kroll also played Lola Skumpy and Coach Steve, Andrew's hormone monster, Maury, and Nick's hormone monster, Rick.Kroll is known for starring in the FX comedy "The League," creating and starring in his own sketch series "Kroll Show," and creating the "Big Mouth" spinoff series "Human Resources." John Mulaney plays Andrew Glouberman. John Mulaney plays Andrew, who is inspired by series co-creator Andrew Goldberg. Courtesy of Netflix Andrew Glouberman, a boy obsessed with masturbation, is Nick Birch's best friend who joins him on his adventure through puberty.John Mulaney, a comedian and former "Saturday Night Live" writer, plays the character. Mulaney has starred in other animated movies, including "Puss in Boots: The Last Wish" and "Spider-Man: Into the Spider-Verse." Jessi Klein plays Jessi Glaser. Jessi Klein is a producer and writer. Charley Gallay / Getty Images for Netflix / Courtesy of Netflix Jessi Klein plays Jessi Glaser, a close friend of Nick and Andrew's who explores her sexuality and struggles with depression and her parents' divorce.Klein is best known for her writing and producing work, having previously produced "Inside Amy Schumer," "Transparent," and "Dead to Me." Maya Rudolph plays Connie LaCienega and Diane Birch. Maya Rudolph has won four Emmys for her performance as Connie. Will Heath / NBC via Getty Images / Courtesy of Netflix Maya Rudolph plays two characters in the series — Connie LaCienega, the hormone monster for Jessi, and Diane Birch, Nick's mother.Rudolph, who rose to fame as a cast member on "Saturday Night Live," has won four primetime Emmy Awards for her performance in "Big Mouth" and has starred in numerous movies and TV shows, including "Bridesmaids," "The Good Place," and "The Lego Movie 2." Ayo Edebiri plays Missy Foreman-Greenwald. Ayo Edebiri played Missy from seasons five to eight. Charley Gallay / Getty Images for Netflix / Courtesy of Netflix Missy is a nerdy biracial classmate of Andrew, Jessi, and Nick's.In the first four seasons, Jenny Slate voiced the character, but she stepped down from the role in 2020, announcing on Instagram that black people should play black characters.Slate was replaced with Ayo Edebiri as Missy began to explore her Black identity in the show.Edebiri is best known for her breakout roles in the 2020s in "Bottoms" and "The Bear." Thandiwe Newton plays Mona. Thandiwe Newton plays a British hormone monster. Rodin Eckenroth / Film Magic / Getty / Courtesy of Netflix Thandiwe Newton played Missy's British hormone monster, Mona.Newton is known for starring in "Westworld," "Mission: Impossible II," and "Solo: A Star Wars Story." Jason Mantzoukas plays Jay Bilzerian. Jason Mantzoukas is known for playing chaotic characters like Jay. Charley Gallay / Getty Images for Netflix / Courtesy of Netflix Jay Bilzerian, a sex-obsessed bisexual boy, is another friend of Andrew, Nick, and Jessi's.Mantzoukas is a comedian who has previously played equally wacky characters in "Brooklyn Nine-Nine," "The Good Place," and "The League." Andrew Rannells plays Matthew MacDell. Andrew Rannells is the voice behind Matthew. Charley Gallay / Getty Images for Netflix Matthew MacDell, a gossipy gay student, was initially a secondary character in the first few seasons but became one of the main characters after season 3, developing relationships with Jay and Jessi.Broadway and screen actor Andrew Rannells has starred in "The Prom" and "Girls" and has a vibrant voice-acting career, appearing on shows like "Sonic X," "Pokémon," and "Invincible." David Thewlis plays The Shame Wizard. David Thewlis plays a spectre known as The Shame Wizard. Lisa Maree Williams / Getty Images / Courtesy of Netflix David Thewlis joined the cast in season two as the Shame Wizard, who will mock and bully the children to amplify their shame around their mistakes.Thewlis previously starred in multiple "Harry Potter" movies, "Wonder Woman," and "The Theory of Everything." Jean Smart plays Depression Kitty. Jean Smart played Depression Kitty since season two. Frazer Harrison / Getty Images / Courtesy of Netflix Depression Kitty first shows up in season two after Jessi starts to develop strong negative emotions amid her parents' divorce. Since then, Depression Kitty has made a few appearances across the show.Jean Smart, an Emmy-winning actor who stars in "Hacks," played Depression Kitty. Maria Bamford plays Tito the Anxiety Mosquito. Tito (Maria Bamford) has had recurring appearances since season four. Dia Dipasupil / Getty Images / Courtesy of Netflix. Tito the Anxiety Mosquito embodies the children's anxiety, first appearing in season four. Comedian Maria Bamford is known for her comedy specials as well as her Netflix show "Lady Dynamite." Zazie Beetz plays Danni. Zazie Beetz only starred in season 7. Amy Sussman / Getty Images / Netflix Danni is a student Nick meets in season seven when considering attending a private school.Zazie Beetz is known for her roles in "Atlanta," "Deadpool 2," "Joker," and "Bullet Train." Megan Thee Stallion plays Megan. Megan Thee Stallion made a cameo in "Big Mouth" season 7 as Megan the hormone monstress. David Crotty / Patrick McMullan via Getty Images / Netflix In season seven, Megan Thee Stallion guest stars as Megan, a hormone monster for Danni.Megan Thee Stallion is better known for her rapping career, though she has also starred in Disney+'s "She-Hulk: Attorney At Law" and the 2023 movie "Dicks: The Musical." Jordan Peele plays the ghost of Duke Ellington. The ghost of Duke Ellington (Jordan Peele) was a major supporting character in the first few seasons. Unique Nicole / WireImage / Netflix One of Nick's friends is the ghost of jazz pianist Duke Ellington, who lives in the teen's attic.Jordan Peele is the voice behind the ghost. He also played Missy's father, Cyrus Foreman-Greenwald.Peele is an Oscar-winning horror director and comedy actor best known for directing "Get Out," "Nope," and "Us" and starring in "Key and Peele." Brian Tyree Henry plays Elijah. Brian Tyree Henry joined the cast in season six. Jamie McCarthy / Getty Images / Netflix Elijah, an asexual Christian student, appears in seasons six and seven, building a relationship with Missy. They broke up after graduating from middle school.Brian Tyree Henry, known for his roles in "Atlanta," "Bullet Train," and Marvel's "Eternals," plays Elijah. Henry has voice acting experience from starring in the "Spider-Verse" movies as Miles Morales' father, Jefferson. Natasha Lyonne plays Ms. Dunn. Natasha Lyonne stars as a sex-ed teacher in "Big Mouth" season eight. The Hapa Blonde / GC Images / Getty Images / Courtesy of Netflix Natasha Lyonne guest stars in the final season as sex-ed teacher Ms. Dunn. Lyonne has also made cameos in previous seasons playing Suzette Saint James, Jay's pillow girlfriend, and Nadia Vulvokov, the character Lyonne plays in Netflix's "Russian Doll."Lyonne is best known for starring in "American Pie," "Orange is the New Black," and "Poker Face." Ali Wong plays Ali. Ali Wong joined the cast in season three, playing a transfer student. Jeff Kravitz / FilmMagic via Getty Images Ali Wong joined "Big Mouth" in season three, playing the pansexual transfer student Ali.Wong is a comedian who has previously starred in other Netflix originals like "Beef" and "Always Be My Maybe." Keke Palmer plays Rochelle. Keke Palmer is the voice actor behind the "Big Mouth" character Rochelle. Emma McIntyre / WireImage / Courtesy of Netflix "Big Mouth" season five introduced the concept of Hateworms and Lovebugs, who strengthen the children's emotions. Rochelle, played by Keke Palmer, was Missy's Hateworm but later transformed into her Lovebug.Palmer is best known for starring in "True Jackson, VP," "One of Them Days," and "Nope."

The humanoid robots are fighting.   Image: Unitree Get the Popular Science daily newsletter💡 Breakthroughs, discoveries, and DIY tips sent every weekday. After decades of being tortured, shoved, kicked, burned, and bludgeoned, robots are finally getting their chance to fight back. Sort of.  This weekend, Chinese robotics maker Unitree says it will livestream the world’s first boxing match between two of its humanoid robots. The event, titled Unitree Iron Fist King: Awakening, will feature a face-off between two of Unitree’s 4.3-foot-tall G1 robots. The robots will reportedly be remotely controlled by human engineers, though they are also expected to demonstrate some autonomous, pre-programmed actions as well. Earlier this week, the two robots previewed some of their moves at an elementary school in Hangzhou, China. Video released by Unitree earlier this month shows the robots, boxing gloves strapped on, “training” with their human coaches. The petite robots throw a few hooks with their arms before being pushed to the ground. One quickly gets back up and, after briefly struggling to face the right direction, spins around and delivers a straight kick, 300-style. Unitree claims its robots use a motion-capture training system that helps them learn from past mistakes and improve over time. The training video also shows the two robots briefly sparring with each other. The clacking sound of steel fills the room as they exchange a flurry of punches. At one point, both simultaneously deliver knee kicks to each other’s groin area, sending the robot in blue gear tumbling to the ground. “The robot is actively learning even more here skills,” the company notes in a caption towards the end of the video.  Humans have a long history of forcing robots to fight  The human tendency to force robots to fight for our amusement isn’t entirely new. The show Battle Bots, which dates back to the late 1990s revolved around engineers creating and designing remote-controlled robots, often armed to the teeth with electric saws and flamethrowers, and forcing them to duke it out. Many, many robots were reduced to scrap metal over the show’s 12 seasons.  Since then, engineers around the world have been experimenting with new ways to teach bipedal, humanoid robots how to throw punches and land kicks without stumbling or falling. Sometimes these machines are remotely controlled by human operators. In other cases, semi-autonomous robots have learned to “mirror” physical movements observed in humans. More advanced autonomous robots, like those being developed by Boston Dynamics and Figure, can move around their environment and perform pre-programmed actions. Neither of those companies, it’s worth noting, have announced any plans to make their robots fight.  China is quickly becoming a center stage for public displays of humanoid robot athletic competition. Last month, more than 20 robotics companies entered their robots into a half-marathon race in Beijing, where they competed against each other and human runners. The results were underwhelming. Media reports from the event claimed many of the machines failed to make it past the starting line. Others veered off course, with one reportedly even crashing into a barrier. The first robot to cross the finish line—a machine designed by the Beijing Humanoid Robot Innovation Center—did so nearly an hour and forty minutes after the first human completed the race. Only six robots finished.