Podcasts about Carper

Next month, as November's election winners are sworn in, one name will be notably absent from the roster of Delaware officeholders. For the first time in nearly 50 years, Tom Carper will not be serving the people of Delaware after announcing in May 2023 that he would not seek another term in the U.S. Senate.Carper departs after stints as Delaware State Treasurer, Congressman, Governor, and U.S. Senator, and his 14-0 record running for statewide office in the First State is unprecedented.Contributor Larry Nagengast recently sat down with Carper to reflect on his 48-year political career and his legacy as one of Delaware's most iconic politicians.

On this episode of Coffee, Country & Cody — we welcome Melissa Carper and The Herculeons!   0:00 - Welcome / What’s Coming Up 2:17 - Entertainment with Kelly Sutton 6:42 - Interview with Melissa Carper 10:42 - Interview with The Hercules!   Nothing gets a morning started better than “Coffee, Country and Cody.” The show’s namesake is Country Music Disc Jockey Hall of Famer and affable television personality Bill Cody. Joining Bill is his producer/sidekick/sports guy/fellow brilliant conversationalist, Charlie Mattos. And rounding out WSM’s dynamic morning crew is Kelly Sutton, Nashville’s go-to entertainment journalist. Together, Bill, Charlie and Kelly start every weekday off with great music—country, bluegrass, Americana, Opry cuts, and live studio guests, the latest news, entertaining features, and more.   Coffee, Country & Cody airs LIVE Monday - Friday! You can listen on WSM 650 AM, and watch on Circle Country through the CircleNow app, and stream on Roku, Samsung TV Plus, Peacock, Vizio, Xumo, Redbox, Sling, and Fubo!   About WSM Radio: WSM is the most famed country music radio station in the world. Each day since it first signed on in 1925, the station has shared country, bluegrass, and Americana music, as well as the excitement of Music City with friends in Middle Tennessee and listeners around the world. Listen anytime on 650 AM, WSMradio.com, or our free mobile app.   Connect with WSM Radio: Visit the WSM Radio WEBSITE: http://bit.ly/650AMWSM Follow WSM Radio on TikTok:  https://www.tiktok.com/@wsmradio Like WSM Radio on FACEBOOK: http://bit.ly/WSMRadioFB Check out WSM Radio on INSTAGRAM: http://bit.ly/WSMRadioInsta Follow WSM Radio on X: http://bit.ly/WSMRadioTweets Listen to WSM Radio LIVE: http://bit.ly/WSMListenLive Listen to WSM on iHeartRadio: https://www.iheart.com/live/wsm-radio...

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This week we welcome the self described "ramblin' soul" that is singer-songwriter Melissa Carper, the Austin, TX treasure who's been highly acclaimed by NPR, Rolling Stone, and No Depression. Melissa introduces us to her rescue dog Georgia Peach who is suspected to be about 10 years old and looks to be part Whippet and part Mountain Cur. We also can't have a conversation about dogs without including Betty Boo who was a Black Lab/American Bulldog mix and had a profound impact on Melissa. Melissa's latest album Borned in Ya was released on July 19th and is brimming with her signature blend of jazz, vintage R&B, and old-school country. To order and see tour dates visit melissacarper.com Melissa's shout out goes to the Doris Day Animal Foundation that was founded in 1978 as the Doris Day Pet Foundation by legendary performer, with a straightforward mission that continues to this day:  to help animals and the people who love them.  As a grant-giving charity, DDAF funds other 501(c)(3) organizations across the United States that directly care for and protect animals. To learn more about their programs, scholarships and grants visit dorisdayanimalfoundation.org For more pics and clips from this conversation follow the podcast on Instagram at rockerdogpodcast

We're into a new week and the July 2024 New Music train steams on. Enrique Cruz and Jason Goebel are on the controls today, giving you the lowdown on new music from Melissa Carper, Johnny Blue Skies and Phish.  Rockin' the Suburbs on Apple Podcasts/iTunes or other podcast platforms, including audioBoom, Spotify, Google Podcasts, Amazon, iHeart, Stitcher and TuneIn. Or listen at SuburbsPod.com. Please rate/review the show on Apple Podcasts and share it with your friends. Visit our website at SuburbsPod.com Email Jim & Patrick at rock@suburbspod.com Follow us on the Threads, Facebook or Instagram @suburbspod If you're glad or sad or high, call the Suburban Party Line — 612-440-1984. Theme music: "Ascension," originally by Quartjar, covered by Frank Muffin. Visit quartjar.bandcamp.com and frankmuffin.bandcamp.com.

Don't miss out as the gang (Geek, Brian & Thomas) dives deep this week with Pro Angler Eddie Carper, who reveals the game-changing email he received from the MLF Tackle Warehouse Series! This highly-anticipated message from the top series seeks anglers' insights on the revolutionary changes that could transform bass fishing forever. If you're passionate about tournament bass fishing, this is the one episode you absolutely can't afford to miss!Click to Join our Patreon Become a supporter of this podcast: https://www.spreaker.com/podcast/bass-cast-radio--1838782/support.

“Ben Carper Responds to Jason Elliot on Carper Residency” “The Disaster that will be Sheri Biggs” “Jason Elliot Responds to Ben Carper Interview” “Text Line Responds to Run off Elections” 

Countdown to the 2024 1st Presidential Debate, Runoff Elections TOMORROW!!!, Joined by Candidates and Special Guests: Stephen Brown, Noel Fritsch, Ben Carper and Jason Elliot.

“Interview with Special Guest Rep. Benton Blount” “Obey the Mob” “Columbia College Dropped Charges” “Eliot vs Carper”

“Josh Kimbrell Rebuts Ben Carper's Claims” “Bump Stock Ban Overturned, Experts Weigh In” “The Bed That Hunter Biden Has Made” “You Voice Your Concerns About Josh Kimbrell's Response”

Who's Spying On Ben Carper? | Can't Miss Moments https://www.audacy.com/989word The Charlie James Show Listen on Spotify : https://spoti.fi/3MXOvGP Apple Podcasts: https://podcasts.apple.com/us/podcast/the-charlie-james-show-podcast/id1547262821 Follow us on Social Media Join our Live Stream Weekdays - 3pm to 7pm  Facebook: https://www.facebook.com/989word Rumble: https://rumble.com/c/c-2031096 X: https://twitter.com/989word Instagram: https://www.instagram.com/989word/ "Red Meat, Greenville." 06/14/24

Recorded from my living room at home on the fringes of downtown Winnipeg, Manitoba, Canada, Episode 004 of the Boots & Saddle [2.0] Show was a spirited affair featuring a fantastic mix of classic cuts and hot new jams. - - - BOOTS & SADDLE (2.0) | Episode 004 INTRO & THEME: The Boots & Saddle Jingle - Boots Graham [w. Catherine Robertson] (2024) Chaparral - Buck Owens' Buckaroos – A Night On The Town (1968) Shufflin' in to the Saddle: 1.  If She Could See Me Now - Ray Price (Night Life - 1963) Beautiful Country Music by Beautiful Country Music Singers: 2. Fist City - Loretta Lynn (Fist City - 1968) 3. Love Bug - George Jones (New Country Hits - 1965) 4. If You Won't Tell - Connie Smith (Miss Smith Goes to Nashville - 1966) New & Recent Releases: 5. I Only Exist [feat. Isaac Gibson] - Kelsey Waldon (There's Always A Song - 2024 6. Better Safe Than Sober - The Honkytonk Wranglers (Single - 2024) 7. A Thousand Ways - Wonder Women of Country (Willis, Carper, Leigh - 2024) 8. Make It Back Home - Pat Reedy (Make It Back Home  - 2024) Round-Up of “lost” Canadian Country [1989 Edition]: 9. Scene of the Crime - Lori Yates (Can't Stop the Girl - 1989) 10. The Legend of Dick Nolan - Barry Smith (Single - 1989) 11. Hello Again - Anita Perras (Touch My Heart - 1989) 2023 Highlights + Outro: 12. California poppy - Theo Lawrence (Chérie - 2023) 13. Lowland Trail - Margo Cilker (Valley Of Heart's Delight - 2023) You Win Again (instrumental) - Jeff Bradshaw & Dave Hamilton (Swingin' Country Dance Toons - 2003) 14. Half Forgotten Tunes - Ags Connolly (Siempre - 2023)  Closing/Oh! Susanna (show 11) - Hank Williams (The Garden Spot Programs, 1950)

We will discuss tonight's Run For The Wall event in Nitro, plus Kanawha Circuit Judge-elect Rich Lindsay, Republican strategist Greg Thomas, more on the release of the Carper body cam footage, the latest on the Manchin rumors and more. See you after the news at 9:00.

Hosted by Sean Burns, Boots & Saddle officially returns from our 2-year "semi-permanent hiatus" with Episode 001 of the relaunched, revamped program. . . . BOOTS & SADDLE (2.0) | Episode 001 INTRO & THEME: The Boots & Saddle Jingle - Boots Graham [w. Catherine Robertson] (2024) Chaparral - Buck Owens' Buckaroos – A Night On The Town (1968) Shufflin' in to the Saddle: 1. Big City - Merle Haggard (Big City - 1981)  Beautiful Country Music by Beautiful Country Music Singers: 2. There She Goes - Carl Smith (Single - 1955) 3. Little Pink Mack - Kay Adams (Wheels & Tears - 1966) 4. How's It Feel - Justin Tubb (Single - 1961)  New & Recent Releases: 5. Long Drives and Lonesome Mornings - Pat Reedy (Make It Back Home - 2024) 6. Losing More - Nicolette and The Nobodies (The Long Way - 2024)  7. The More You Live - Russell deCarle (The End Of The Road - 2024) 8. Hanging On To You - Wonder Women of Country (Willis, Carper, Leigh - 2024) Regional Round-Up of “lost” Canadian Country Music: 9. My Home in Saskatchewan - Chef Adams (Singer/Songwriter - 1969) 10. I'll Be Lonesome When You Are Gone - June Pasher (Your Cheating Heart And Other Country Favourites - 1962*) 11. I Don't Want To Be Me - Mickey McGivern & The Mustangs Featuring Billy Adams (Hard Times - 1967) 12. It's All Over - Fern Dauth (Fern Dauth Of Country Music Hall - 1967) Outro: You Win Again (instrumental) - Jeff Bradshaw & Dave Hamilton (Swingin' Country Dance Toons - 2003) 13. Badly Broken Man - Scotty Campbell (Damned If I Recall - 1999) Closing/Oh! Susanna (show 11) - Hank Williams (The Garden Spot Programs, 1950)

Ralph welcomes back medical journalist and New York Times bestselling author, Jean Carper, to elaborate on her latest book, “100 LIFE OR DEATH FOODS: A Scientific Guide to Which Foods Prolong Life or Kill You Prematurely.” Plus, the latest news about Boeing and the UAW.Jean Carper is a medical journalist, and wrote “EatSmart” (a popular weekly column on nutrition, every week for USA Weekend Magazine)  from 1994 until 2008; she is still a contributing editor, writing health and nutrition articles. Ms. Carper is also a former CNN medical correspondent and director of the documentary Monster in the Mind. She is the best-selling author of 25 books, mostly on nutrition and health. Her latest book is 100 LIFE OR DEATH FOODS: A Scientific Guide to Which Foods Prolong Life or Kill You Prematurely.The reason I wrote the book was that I knew there is no other book like this. Nobody has taken a scientific look at all the studies that are being done on specific foods with conclusions as to how they are going to affect longevity. It is a totally new field. It really only started several years ago where scientists are getting interested in this. I thought of all the things that would be the most interesting about a food, and whether or not you wanted to eat it would be, “Oh, how long does it prolong my life? Or on the other hand, is it likely to shorten my life?”Jean CarperLess-developed countries with their natural food from over the history of their cultures are very often far superior [in longevity studies] to the so-called corporatized Western diet.Ralph NaderIn Case You Haven't Heard with Francesco DeSantis1. The International Criminal Court at the Hague is preparing to hand down indictments to Israeli officials for committing war crimes. The Guardian reports the indicted are expected to include authoritarian Prime Minister Benjamin Netanyahu and Defense Minister Yoav Gallant, among others. These indictments will likely focus on Netanyahu's strategy of intentional starvation in Gaza. Yet, lest one think that the United States actually believes in the “rules based international order,” they have touted so frequently, the Biden administration will not allow these indictments to be effectuated, baselessly claiming that the ICC does not have jurisdiction in Israel. Democracy Now! reports State Department spokesman Vedant Patel told the press “Since this president has come into office, we have worked to reset our relationship with the ICC, and we are in contact with the court on a range of issues, including in connection to the court's important work on Darfur, on Ukraine, on Sudan, as well. But on this investigation, our position is clear: We continue to believe that the ICC does not have jurisdiction over the Palestinian situation.” Former Human Rights Watch Executive Director Kenneth Roth – who has faced retribution for his past criticism of Israel – called this “the height of hypocrisy.”2. Even as the United States shields Israel from international legal consequences for its crimes, an internal state department memo indicates the American diplomatic corps is increasingly skeptical of the pariah state. Reuters reports “senior U.S. officials have advised Secretary of State Antony Blinken that they do not find ‘credible or reliable' Israel's assurances that it is using U.S.-supplied weapons in accordance with international humanitarian law.” This memo includes “eight examples of Israeli military actions that the officials said raise "serious questions" about potential violations of international humanitarian law…[including]  repeatedly striking protected sites and civilian infrastructure; "unconscionably high levels of civilian harm to military advantage"; taking little action to investigate violations or to hold to account those responsible for significant civilian harm and "killing humanitarian workers and journalists at an unprecedented rate."” The State Department however will only release a “complete assessment of credibility” in its May 8th report to Congress.3. On Tuesday, the Guardian reports, an army of NYPD officers – including hundreds of armed officers in riot gear and heavy vehicles such as police busses, MRAPs, and “the Bear,” a ladder truck used to breach upper story windows – stormed the campus of Columbia University and carried out mass arrests at the college's Hamilton Hall – which had been non-violently occupied by students and renamed Hind's Hall after Hind Rajab, a six-year old Palestinian girl murdered by the IDF. Hamilton Hall was among the buildings occupied by anti-Vietnam War Protesters during the Columbia Uprising of 1968. Mayor Eric Adams used as a pretext for this militarized police action a claim that the student protest had been “co-opted” by “outside agitators”; there has been no evidence presented to support this claim. The NYPD also threatened to arrest student journalists, and the Columbia Journalism School Dean Jelani Cobb, per Samantha Gross of the Boston Globe, and videos show the cops arresting legal observers and medics. Columbia University President, the Anglo-Egyptian Baroness Minouche Shafik, has requested that the NYPD continue to occupy the Morningside Heights campus until May 17th.4. At the University of California Los Angeles, the New York Times reports “U.C.L.A. asked for officers after a clash between pro-Palestinian demonstrators and counterprotesters grew heated overnight.” This misleading report fails to clarify that, as Alejandra Caraballo of Harvard Law puts it “the police stood aside and let a pro Israeli lynch mob run wild at UCLA. They did nothing for two hours as violent Zionists assaulted students, launched fireworks into the encampment, and sprayed mace on students.” The accompanying videos must be seen to be believed. This is yet another glaring example of media manipulation on behalf of Zionist aggression against non-violent student protesters.5. In the nation's capital, a peaceful pro-Palestine encampment at the George Washington University continues to hold in the face of increasing pressure. The Washington Post reports that the university requested the D.C. Metropolitan Police Department to clear the encampment last week, but the cops demurred. The Post article cites an unnamed D.C. official who “said they had flashbacks to June 2020, when images of mostly peaceful protesters being forcefully shoved out of Lafayette Square by U.S. Park Police officers with batons and chemical irritants made national news.” The university has issued temporary suspensions and did attempt to clear the encampment over the weekend, but failed to do so. Now however, congressional Republicans are heaping pressure upon the university and District of Columbia Mayor Bowser. According to the GW Hatchet, “[Representatives] Virginia Foxx and James Comer — who chair the House Committee on Education and the Workforce and the Committee on Oversight and Accountability, respectively — wrote [in letter to Bowser and MPD Chief Pamela Smith] that they were “alarmed” by the Metropolitan Police Department's reported refusal to clear the encampment.” and threatened to take legislative action. Senator Tom Cotton, infamous for his New York Times op-ed calling for the deployment of the national guard to shut down Black Lives Matter protests in 2020, sent a letter to Bowser on Tuesday, writing “Whether it is due to incompetence or sympathy for the cause of these Hamas supporters, you are failing to protect the rights of law-abiding citizens by letting a terrorist-supporting mob take over a large area of a university…Your actions are a good reminder of why Washington, D.C. must never become a state.” So far, the District's leadership has exercised a rare and commendable restraint. One can only hope that continues.6. Looking beyond individual campuses, the Appeal reports over 1,400 students and staff have been arrested at “protest encampments or…sit-ins on more than 70 college campuses across 32 states during the past month.”  This piece followed up on these arrests by contacting prosecutors and city attorneys' offices in every one of these jurisdictions – and found that “only two offices said they would not charge people for peacefully protesting.” These were “ Sam Bregman, the prosecutor for Bernalillo County, New Mexico, [which] includes the University of New Mexico's Albuquerque campus….[and] Matthew Van Houten, the prosecutor overseeing Cornell University in Ithaca, New York.” Incredibly, this piece was published even before the recent mass arrests at Columbia and the City College of New York, which are estimated at nearly 300, per CNN.7. Bringing the civil war within the Democratic Party on this issue into full view, the College Democrats of America – the official student outreach arm of the DNC – has issued a statement commending the “heroic actions on the part of students...for an end to the war in Palestine…[and] for an immediate permanent ceasefire.” This statement goes on to say “Arresting, suspending, and evicting students without any due process is not only legally dubious but morally reprehensible,”  and excoriates the White House for taking “the mistaken route of a bear hug strategy for Netanyahu and a cold shoulder strategy for its own base,” noting that “Each day that Democrats fail to stand united for a permanent ceasefire…more and more youth find themselves disillusioned with the party.”8. Moving beyond Palestine, hard as that is, the American Prospect is out with a chilling new story on Boeing. This report documents how the late Boeing whistle-blower John “Swampy” Barnett – who died under deeply mysterious circumstances during his deposition against the aviation titan last month – was ignored, mocked, and harassed by his corporate overlords. When he tried to raise the alarm that Boeing's practices could be in violation of Section 38 of the United States Criminal code “The whole room…burst out laughing.” When he found planes riddled with defective and nonconforming parts and tried to report it, a supervisor emphatically declared “We're not going to report anything to the FAA.” Yet even more than Boeing's rancid corporate culture, this piece takes aim and corporate criminal law – specifically the Y2K era AIR 21 law which “effectively immunizes airplane manufacturers…from suffering any legal repercussions from the testimony of their own workers.” Per this law, “the exclusive legal remedy available to aviation industry whistleblowers who suffer retaliation for reporting safety violations involves filing a complaint within 90 days of the first instance of alleged retaliation with a secret court administered by the Occupational Safety and Health Administration that lacks subpoena power, takes five years or longer to rule in many cases, and rules against whistleblowers an astounding 97 percent of the time, according to the Government Accountability Project.” No wonder Boeing acts as though they are above the law.9. The United Auto Workers union continues to rack up victories. On Tuesday, More Perfect Union reported “ Mercedes-Benz has abruptly replaced its U.S. CEO in an effort to undercut the union drive at Mercedes's plant in Alabama…In a video shown to workers…new CEO Federico Kochlowski admits that ‘many of you' want change and [promised] improvements.” As Jonah Furman, Communications Director for UAW, notes “Mercedes workers have already:-- killed two-tier wages-- gotten their UAW pay bump-- [and] fired their bossand they haven't even voted yet!If that's what you get for just *talking* union, imagine what you can win when you *join* the union.”Moreover, UAW President Shawn Fain issued a statement decrying the mass arrests of anti-war protesters, writing “The UAW will never support the...intimidation of those exercising their right to protest, strike, or speak out against injustice…This war is wrong, and this response against students and academic workers, many of them UAW members, is wrong…if you can't take the outcry, stop supporting this war.”10. Finally, the New York Daily News's Chris Sommerfledt reports “[New York City's] largest cop union [the Police Benevolent Association] is suing Police Commissioner Ed Caban and Mayor Adams for implementing a new “zero tolerance” policy on NYPD officers using steroids or other performance-enhancing drugs.” The fact that the PBA is suing this ardently pro-cop mayoral administration is alarming enough, but the fact that enough NYPD officers are using steroids to warrant this policy – and enough for the union to step in on their behalf – raises an even more alarming question: how many roid-rage fueled NYPD cops are terrorizing marginalized people on the streets of New York City? Perhaps this could explain some of the NYPD's outrageous, disproportionately violent behavior in recent years.This has been Francesco DeSantis, with In Case You Haven't Heard. Get full access to Ralph Nader Radio Hour at www.ralphnaderradiohour.com/subscribe

This week on the banjo chat!  We have Melissa Carper! We are chatting about being on the road with her band, her debut at the Grand Ole Opry and how she writes songs and stays close to her roots.  We talk about her transformation from being a side person, to how her creativity came alive, and what was stifling her creativity.  Healthy alternatives to drinking and how to get sleep on the road! Also, what has kept her on her path when dealing with frustration, playing in bars over the years.  How she kept on believing in what she could do!   https://melissacarper.bandcamp.com https://www.melissacarper.com https://patreon.com/banjochat

District 6 Candidate for Senate Ben Carper Responds to Timmons    0:00.000        Text Line Responds to Timmons TSA Interview    8:58.391  Death to America Democrats    17:46.574     Basic Economics with Tara     27:18.933    

Coming up this morning, of course the big story is the flooding. Kanawha County Commissioner Kent Carper and Charleston Mayor Amy Shuler Goodwin are here, plus Michael Lipton from the West Virginia Music Hall of Fame, Eric Mani from the Red Cross and more on a special fundraiser tomorrow in Nitro.

Today's show will primarily be focused on the weather and the storm damage in the Kanawha Valley. Kanawha County Commissioners Carper, Wheeler and Salango will all be on this morning, plus Goodwin Chief of Staff Matt Sutton and Delegate Mike Pushkin.

  The Friday Five for March 22, 2024: #FierceMadness EWG's Dirty Dozen & Clean Fifteen iPad Update & This Week's Streaming Pick FOMC March 2024 Meeting The DUALS Act of 2024   What would you rather? Read a story, listen to it, or watch the movie? VOTE HERE!   #FierceMadness: #FierceMadness: Grab a bracket and vote for the most overused buzzword in healthcare! https://www.fiercehealthcare.com/special-reports/fiercemadness-grab-bracket-and-help-us-find-biggest-buzzword-healthcare Fierce Madness Bracket PDF: https://s3.amazonaws.com/publiceditorial.qtxasset.com/Fierce+Madness+Round+1+Bracket.pdf   Environment Working Group's Dirty Dozen & Clean Fifteen: 2024′s ‘Dirty Dozen': The 12 fruits and vegetables with the most pesticides—and tips for enjoying them safely: https://www.cnbc.com/2024/03/20/dirty-dozen-2024-12-fruits-and-vegetables-with-the-most-pesticides.html Blueberries, strawberries again on the ‘Dirty Dozen' list: https://www.cnn.com/2024/03/19/health/dirty-dozen-produce-pesticides-2024-wellness/index.html 'Dirty Dozen' Guide Shows 95% of These Fruits and Veggies Tested Positive for Pesticides: https://www.commondreams.org/news/ewg-2024-dirty-dozen-pesticides EWG's 2024 Shopper's Guide to Pesticides in Produce™: The Dirty Dozen™ is packed with fungicides that can disrupt human hormones: https://www.ewg.org/news-insights/news-release/2024/03/ewgs-2024-shoppers-guide-pesticides-producetm-dirty-dozentm The Clean Fifteen (EWG Official List): https://www.ewg.org/foodnews/clean-fifteen.php The Dirty Dozen (EWG Official List): https://www.ewg.org/foodnews/dirty-dozen.php   RR – iPad Update & This Week's Streaming Pick Apple's iPad Pro could come with a matte display: https://mashable.com/article/apple-ipad-pro-matte-display-rumors Claim of iPad announcement on March 26 ‘not true' – Gurman: https://9to5mac.com/2024/03/21/ipad-announcement/ Gurman: No iPad Announcement Planned for March 26: https://www.macrumors.com/2024/03/21/gurman-no-ipad-announcement-march-26/ New iPad Air already shipping to US ahead of launch — and there's a new size this time around: https://www.tomsguide.com/tablets/ipads/new-ipad-air-already-shipping-to-us-ahead-of-launch-and-theres-a-new-size-this-time-around New iPad Pros and iPad Airs could land on March 26, but one model might be missing: https://www.techradar.com/tablets/ipad/new-ipad-pros-and-ipad-airs-could-land-on-march-26-but-one-model-might-be-missing The Three-Body Problem: The 'unfilmable' Chinese sci-fi novel set to be Netflix's new hit 3 Body Problem: https://www.bbc.com/culture/article/20240319-3-body-problem-china-censored-sci-fi-netflix-hit   FOMC March 2024 Meeting: Consumer Price Index (CPI) February 2024: https://www.bls.gov/news.release/pdf/cpi.pdf  Consumer prices up 3.1 percent from January 2023 to January 2024: https://www.bls.gov/opub/ted/2024/consumer-prices-up-3-1-percent-from-january-2023-to-january-2024.htm Fed Holds Rates Steady and Projects Three Cuts This Year: https://www.nytimes.com/2024/03/20/business/fed-meeting-interest-rates.html Federal Open Market Committee 2024 Calendar: https://www.federalreserve.gov/monetarypolicy/fomccalendars.htm Fed meeting recap: Everything Powell said during Wednesday's market-moving news conference: https://www.cnbc.com/2024/03/20/fed-meeting-today-live-updates-on-march-fed-rate-decision.html Personal Income and Outlays, January 2024: https://www.bea.gov/news/2024/personal-income-and-outlays-january-2024   The DUALS Act of 2024: Cassidy, Carper, Cornyn, Warner, Scott, Menendez Comprehensive Legislation Improve Care For Patients Jointly Enrolled In Medicare And Medicaid: https://www.cassidy.senate.gov/newsroom/press-releases/cassidy-carper-cornyn-warner-scott-menendez-comprehensive-legislation-improve-care-for-patients-jointly-enrolled-in-medicare-and-medicaid/ Medicare, Medicaid Plans Could Drastically Change: https://www.newsweek.com/duals-act-new-bill-medicare-medicaid-integration-1879855 The Delivering Unified Access to Lifesaving Services Act of 2024: https://www.cassidy.senate.gov/wp-content/uploads/2024/03/Duals-Legislation-One-Pager-Final.pdf Vulnerable Americans are stuck in a Medicare-Medicaid maze. Is a fix in sight? https://www.npr.org/sections/health-shots/2024/03/14/1238386157/vulnerable-americans-are-stuck-in-a-medicare-medicaid-maze-is-a-fix-in-sight   Resources: Agent's Guide to Digital Marketing Resources: https://link.chtbl.com/ASG584    Agent's Guide to Traditional Marketing Resources: https://link.chtbl.com/ASG583 Developing a Retention Mindset ft. Blake Amos (Cigna Healthcare): https://link.chtbl.com/2024BlakeAmos   Health Care Provisions in Biden's 2025 Budget: https://link.chtbl.com/ASGF20240315 How to Be an Adaptable Insurance Agent: https://link.chtbl.com/ASG582   Follow Us on Social! Ritter on Facebook, https://www.facebook.com/RitterIM Instagram, https://www.instagram.com/ritter.insurance.marketing/ LinkedIn, https://www.linkedin.com/company/ritter-insurance-marketing TikTok, https://www.tiktok.com/@ritterim Twitter, https://twitter.com/RitterIM and Youtube, https://www.youtube.com/user/RitterInsurance   Sarah on LinkedIn, https://www.linkedin.com/in/sjrueppel/ Instagram, https://www.instagram.com/thesarahjrueppel/ and Threads, https://www.threads.net/@thesarahjrueppel  Tina on LinkedIn, https://www.linkedin.com/in/tina-lamoreux-6384b7199/ 

Have you ever created a vision board or done a meditation that involved imagery or imaging yourself in a certain situation?  If so, then you have used the technique of visualization.  Visualization is touted as a tool of manifestation culture, an almost magical mystical process of visioning what you want to create and drawing that reality closer.The reality is that visualization is a powerful tool when combined with action in the world.  And here at the crossroads of woo and pragmatism, there is also science backing up its effectiveness.In this episode:Why visualization works (how it affects the brain)Studies showing the power of visualizationDifferent types of visualization practicesHow visualization strengthens abstract thinking and the default network of the brainVisualization to increase creative problem solving and resilienceGet your Nourished for Resilience Workbook Here:  http://www.nourishednervoussystem.com/resilienceworkbookRelated Episodes:Episode 11 - Why What You Think MattersEpisode 14 - This is Your Brain on MeditationReferences:Slimani M, Tod D, Chaabene H, Miarka B, Chamari K. Effects of Mental Imagery on Muscular Strength in Healthy and Patient Participants: A Systematic Review. J Sports Sci Med. 2016 Aug 5;15(3):434-450. PMID: 27803622; PMCID: PMC4974856.Carper, S. K. (n.d.). THE NEUROSCIENCE OF VISUALIZATION: HOW IT CAN IMPACT YOUR LIFE. Visiting Sub Conscious. https://visiting-subconscious.com/sci-visualize-brainSwart, T., MD, PhD (2018). The Source, the secrets of the universe, the science of the brain. HarperOne.Find me at www.nourishednervoussystem.comand @nourishednervoussytem on Instagram

A Carpy Connection's Mark Hunter is today's guest.  Videography, terminal tackle and PBs are on the menu today. Enjoy!

Have you ever got a hot flash just because you are going through customs? Scott Carper had a nightmare scenario coming back in from the Mexico border. He was addicted to pain pills and made a trip across the Mexico border to save some money. When he went through United States Customs his world was forever changed. He knew he has the pills and declared them what he didn't know was what else was in the car. Like a scene from a movie, Scott's life was forever changed. Scott was the prom king and valedictorian in high school. He has a bad car accident that took him on a path to pain meds. Regardless, of the pain and the eventual addiction Scott was a successful business guy in the movie/TV, and eventually ended up in the billboard sign business in the Southwest region of the country. Scott was just released from Leavenworth and has quite the story to share. --- Support this podcast: https://podcasters.spotify.com/pod/show/brent-cassity/support

Jim kicks off November New Music with choice cuts from J Mascis, Mary Timony and Surf Trash. Plus, a John Prine cover by Hayes Carll and Melissa Carper. Get with Rockin' the Suburbs on Apple Podcasts/iTunes or other podcast platforms, like audioBoom, Spotify, Google Podcasts, Amazon, iHeart, Stitcher and TuneIn. Or listen at SuburbsPod.com. Please rate/review the show on Apple Podcasts and share it with your friends. Visit our website at SuburbsPod.com Email Jim & Patrick at rock@suburbspod.com Follow us on the Threads, Facebook or Instagram @suburbspod If you're glad or sad or high, call the Suburban Party Line — 612-440-1984. Theme music: "Ascension," originally by Quartjar, covered by Frank Muffin. Visit quartjar.bandcamp.com and frankmuffin.bandcamp.com

This week joining Hassan in the studio is the River Ouse carping pirate himself Dave Little.Dave needs no introduction he's a top carp angler who has not only published his own book "A Carper's Path" but has also built up and incredible reputation as a river carp specialist.Dave talks about his grounding in fishing and where his love for carp fishing started. He then goes on to chronicle in detail his river fishing on the Great Ouse including a host of the most magical river 30lbers.Now Dave is no one trick pony and he goes on to talk all things fishing on the St Ives complex including his historic capture of Colin. He also talks about some other stand out captures on the Woolpack as well as some recent "guesting".There's one thing for sure Dave has caught them and he is a talented story teller. This podcast goes to show how the unknown river network can be a real carp fishing paradise if you are willing to put in the work.

The Latent Space crew will be at NeurIPS on Tuesday! Reach out with any parties and papers of interest. We have also been incubating a smol daily AI Newsletter and Latent Space University is making progress.Good open models like Llama 2 and Mistral 7B (which has just released an 8x7B MoE model) have enabled their own sub-industry of finetuned variants for a myriad of reasons:* Ownership & Control - you take responsibility for serving the models* Privacy - not having to send data to a third party vendor* Customization - Improving some attribute (censorship, multiturn chat and chain of thought, roleplaying) or benchmark performance (without cheating)Related to improving benchmark performance is the ability to use smaller (7B, 13B) models, by matching the performance of larger models, which have both cost and inference latency benefits.Core to all this work is finetuning, and the emergent finetuning library of choice has been Wing Lian's Axolotl.AxolotlAxolotl is an LLM fine-tuner supporting SotA techniques and optimizations for a variety of common model architectures:It is used by many of the leading open source models:* Teknium: OpenHermes, Trismigestus, CollectiveCognition* OpenOrca: Mistral-OpenOrca, Mistral-SlimOrca* Nous Research: Puffin, Capybara, NousHermes* Pygmalion: Mythalion, Pygmalion* Eric Hartford: Dolphin, Samantha* DiscoResearch: DiscoLM 120B & 70B* OpenAccess AI Collective: Manticore, Minotaur, Jackalope, HippogriffAs finetuning is very formatting dependent, it also provides prompt interfaces and formatters between a range of popular model formats from Stanford's Alpaca and Steven Tey's ShareGPT (which led to Vicuna) to the more NSFW Pygmalion community.Nous Research MeetupWe last talked about Nous at the DevDay Recap at the e/acc “banger rave”. We met Wing at the Nous Research meetup at the a16z offices in San Francisco, where they officially announced their company and future plans:Including Nous Forge:Show NotesWe've already covered the nuances of Dataset Contamination and the problems with “Open Source” in AI, so we won't rehash those topics here but do read/listen to those if you missed it.* Axolotl GitHub and Discord* The Flan paper and dataset* StackLlama model and blogpost* Multipack paper* Our episode with Tri Dao* Mamba state space models - Tri Dao and Albert GuTimestamps* [00:00:00] Introducing Wing* [00:02:34] SF Open Source AI Meetup* [00:04:09] What is Axolotl?* [00:08:01] What is finetuning?* [00:08:52] Open Source Model Zoo* [00:10:53] Benchmarks and Contamination* [00:14:29] The Case for Open Source AI* [00:17:34] Orca and OpenOrca* [00:23:36] DiscoLM and Model Stacking* [00:25:07] Datasets and Evals over Models* [00:29:15] Distilling from GPT4* [00:33:31] Finetuning - LoRA, QLoRA, ReLoRA, GPTQ* [00:41:55] Axolotl vs HF Transformers* [00:48:00] 20x efficiency with StackLlama and Multipack* [00:54:47] Tri Dao and Mamba* [00:59:08] Roadmap for Axolotl* [01:01:20] The Open Source AI CommunityTranscript[00:00:00] Introducing Wing Lian[00:00:00] ​[00:00:00] swyx: Welcome to Latent Space, a special edition with Wing Lien, but also with our new guest host, Alex. Hello, hello. Welcome, welcome. Again, needs no introduction. I think it's like your sixth time on Latent Space already. I think so, yeah. And welcome, Wing. We just met, but you've been very prolific online. Thanks for having me.[00:00:30] Yeah. So you are in town. You're not local. You're in town. You're from Minneapolis?[00:00:35] Wing Lian: Annapolis. Annapolis. It's funny because a lot of people think it's Indianapolis. It's I've got Minneapolis, but I used to live out at least in the San Francisco Bay Area years ago from like 2008 to 2014. So it's fairly familiar here.[00:00:50] swyx: Yep. You're the maintainer of Axolotl now, which we'll get into. You're very, very prolific in the open source AI community, and you're also the founder of the Open Access AI Collective. Yeah. Cool. Awesome. Maybe we can go over a little bit of your backgrounds into tech and then coming into AI, and then we'll cover what[00:01:06] Wing Lian: happens and why you're here.[00:01:08] Yeah. So. Back on tech, so I started years ago, I started way back when I was scraping, Apartment websites for listings and then, and then building like SEO optimized pages and then just throwing Google AdSense on it.[00:01:24] And that got me through like college basically. Is[00:01:27] swyx: that decent money? And what year[00:01:28] Wing Lian: was this? Like 2004, 2005. Yeah, that's decent money. It's like thousand bucks a month. But as a college student, that's like. Gravy. Really good money, right? So, and then there's just too much competition It's just sort of like died off. I was writing stuff in like Perl back then using like like who nobody hosted anything on Perl anymore, right? Still did a little bit more like computer tech support and then software, and web more professionally.[00:01:54] So I spent some time working on applications in the blood industry. I came out to San Francisco for, I was at SGN, so Social Gaming Network, as a startup. They started doing, with Facebook apps, and then they pivoted into doing mobile apps. And then, from there, I spent time.[00:02:14] I've quite a few more startups since then and in the last few years I've been in the music space So like I was at United Masters for a while and then past year I've been at SoundCloud, but not doing that anymore and now that I have a lot more time It's just like all right.[00:02:30] We're going full bore on axolotl and we're gonna we're gonna crush AI So yeah,[00:02:34] SF Open Source AI Meetup[00:02:34] swyx: totally you so you're here in town for the open source. Yeah, I meet up that we had yesterday Yep, yeah, that was amazing. Yeah, it was a big collection. Olama, Noose Research, Alignment Lab, Anyone else that I missed? I mean, Jeremy Howard is his own thing.[00:02:47] Yeah.[00:02:49] And Alex, you're also there. You love to bring SF to the world. Your takes?[00:02:55] Alex Volkov: It's incredible that we recorded a Thursday Eye episode after that one. And LDJ, who's usually co hosts Thursday Eye, just like briefly mentioned, Oh yeah, I talked about it.[00:03:04] Like, I saw Karpathy, and then I talked to Jeremy Howard, and the guy from Mistral came in, and it's like, He's talking about all these, titans of industry, basically, that outside of SF, You just don't meet casually hanging out in the same space. You can't, pull somebody. He ran into the Laylow from Mistral, he ran into him while, drinking water.[00:03:20] He didn't even know he was there. It's just, that type of stuff is really hard to find outside of SF. So, absolutely, absolutely great. And also, presentations from Alignment Labs, presentations from News Research, news issues, talked about. Forge, and some of[00:03:33] swyx: the other stuff they announced. We can say now they're officially a company.[00:03:36] I met Technium.[00:03:37] He[00:03:37] Alex Volkov: came over here. He didn't want to get recorded. But maybe.[00:03:41] Wing Lian: We'll wear him down at some point. Yeah, I'm excited for Forge. They've positioned it as this agentic sort of framework where it's just Drag and drop things and, fill in text with where you want to inject different variables and it opens up all of these potentials for data pipelines now, right?[00:03:56] And using your own local LLMs and not relying on GPT 4 or anything like that. Yeah, yeah,[00:04:02] swyx: good stuff. Okay, so let's maybe go into the Axolotl origin story and then we have, we have some intro or background.[00:04:09] What is Axolotl?[00:04:09] swyx: To do on like the open source model universe and also on fine tuning, but maybe just, since you're talking about your personal journey, what was your personal journey into[00:04:18] Wing Lian: axolotl?[00:04:19] Yeah, so my personal journey started like back in mid March, completely unrelated to AI and axolotl. And it really started, I fell while skiing, I torqued. Great 3 MCL sprain and being sort of like an active person that can no longer be active because the two, couldn't play soccer, because that is requires to have having knees until I, it's healed.[00:04:42] So I. I decided I needed to find something to do to take up my free time. And that became, well, let's learn how to train in, these language models. It was everywhere. So I was like, all right, I'm just going to sit down, learn. I think I used like other, I think I was using like Alpacalora.[00:05:00] Cause I think the Alpaca paper had just came out, come out then. So I was like using Alpacalora repo and sort of like learning how to use like. None of us were like GPU rich back then, and none of us, most of us still we're still all GPU poor, but I was doing what was it, like 4 bit, Alpaca Lord, there was like a 4 bit version where we were doing quant, or 8, no, 8 bit quantizations, and then I think they had released QLOR a little bit later, and I think right when, before QLOR came out, I was already starting to do fine tunes, but having this need to sort of like mix data sets together, and If you've ever looked at all the various different datasets available on HuggingFace, they all have various different prompt formats, and, it's sort of a nightmare, and then I think the other piece is if you've ever tried to fine tune, at least Back then probably the ecosystem's a little better now.[00:05:54] Everybody required that you say, alright, you put your hyperparameters as command line arguments. And so it's always like, well, I now have to go copy and paste my previous thing and to change things out. And I really wanted it. to be in a YAML file because it was more portable and reproducible.[00:06:09] So I was doing that and then the QLOR paper came out. Tim Dettmer announced that and then somebody looked it up for me yesterday and it's like between that announcement it took us seven days to get that integrated into Axolotl, right? Which is like, it's not. I wouldn't say it's really fast, but in a manner that, is in a, a reusable framework, I think it was quite the accomplishment then.[00:06:33] And so we started, picking up traction with people there. And then it's just been building models, and then just iterating what my needs are. So, yeah. Excellent. Yeah. I[00:06:44] Alex Volkov: want to ask, for folks who are listening who never heard of Axolotl, now do you describe how you got there?[00:06:49] Can you, how do you summarize this for folks who maybe haven't fine tuned anything. They know about open source LLM exists, they maybe know like LLAML, what's XLR for somebody who doesn't know. I've never heard of a data set curation[00:07:01] Wing Lian: creation before. We sort of have to take a step back and understand that, when you've got these language models, you have what I think most people refer to as like base models, also known as like foundational models, right?[00:07:15] Where some benefactor, whether it's Meta or Mistral or whoever, has gone and spent all this money. To train these models on huge corpuses of text, right? And these, these corpuses, they're generally good across lots of different things, but they're really good at just saying, talking on and on and on, but they're not good at, following instructions or having chats or anything like that.[00:07:40] So, when you think about fine tuning, it's like Saying, all right, we have this really sort of good generalized, text completion thing, and I want to turn it into something that I can talk to or have, follow instructions. So, I think fine tuning is probably best defined in like that.[00:07:58] swyx: Okay, got it.[00:07:59] And we actually[00:08:01] What is finetuning?[00:08:01] swyx: Do want to make sure that we have like an overall introduction to fine tuning for people because again like trying to make sure that we bring everyone along in this, in this journey. We already went into Loras and QLoras without explaining what[00:08:12] Wing Lian: they are. Oh yes, yes, sorry.[00:08:14] swyx: And so I will put things in my words and you can correct me as, as, as my I'll be the village idiot here.[00:08:21] So, so fine tuning is basically sort of grabbing an open source model off the shelf, and then basically doing further training on it with a custom dataset of your own. Primarily, people use it, think about it as fine tuning for JSON output, or fine tuning for a style of response. Let's say you wanted to tell jokes, or be funny, or be short, or whatever.[00:08:43] Just the open source AI community has really fine tuned in all sorts of different manner. I think we'll go over those those things now. Let's go over those things now, and then we'll talk about fine tuning methods.[00:08:52] Open Source Model Zoo[00:08:52] swyx: So there's a universe of people who fine tune stuff. Yesterday in your slides, you had, I'll just list some of these and then we'll maybe go through some of them, right?[00:08:59] So Technium is personally leading Open Hermes, which is I think the sort of premier model out of the news. news community. There's OpenOrca, which you had a hand in. News, the news research itself also has Capybara and Puffin and all the others. There's Pygmalion, which I've never messed with.[00:09:14] Eric Hartford, I am aware of his Uncensored Models and his Samantha Models. Disco Research with Disco LM. And then you personally have done Manticore, Minotaur, Jackalope, and Hippogriff. What should people know about all these names? Being part of AI Twitter is seeing all these things and going dude, I'm being DDoS'ed by all these things and I don't know how different they are.[00:09:32] What should people know? Yeah, so[00:09:34] Wing Lian: I think on a lot of these models, generally, we like to think of those as sort of general models, so If you think about it, what is GPT 4, what is Chad GPT? It's a good general model, and then, One of the services I think that OpenAI offers is like these fine tunings where you're a business and you have very specific business use cases and you might fine tune for that use case.[00:10:00] All of these models are really just general use case that you can then go and maybe Fine tune another lore over it for your use cases, but they tend to be good. With good being relative, it's open source. Open source AI is still sort of is infancy. So, good is, it's pretty reasonable.[00:10:18] It's probably still better than most, high schoolers at answering questions and being able to like figure things out and, and reasoning skills and math and those sorts of things, right?[00:10:27] swyx: And also as measured on the Hugging[00:10:29] Wing Lian: Face leaderboard. Yes, well, that's like a whole other discussion, right, there's a whole other, group of people who, and I, I mostly agree with them that, benchmarks can be, are pretty bogus these days, LM says, I think they published something recently where, even if you think the dataset's not contaminated, you can go and, find contamination And maybe we should step back and say what contamination is, right?[00:10:53] Benchmarks and Contamination[00:10:53] Wing Lian: So we have all of these data, when you go and do these benchmarks, there's a specific data set where there are these questions and usually it's multiple choice. And what can happen is, well, sometimes someone It puts the question, maybe maliciously, maybe accidentally, into the training dataset, and now the, the, your model knows how to answer the test questions really well, but it doesn't, it hasn't generalized the ability to actually do that[00:11:20] Alex Volkov: right.[00:11:21] We've seen some folks competitively announce models that are like the best at that leaderboard, but then it's, it's quite obvious that, In open source? Yeah, and in that leaderboard, for Hugging Face specific, I don't know if LMCs, if that had suffered, but we, there's been some models that seem to have been competitively trained and some leakage happened into their,[00:11:41] swyx: like, supposal.[00:11:43] I understand, once there's been a credible assertion, Hugging Face actually does take them down, right? Yeah, yeah,[00:11:48] Alex Volkov: which is really hard to know, right?[00:11:50] swyx: It's really hard to know, sometimes it's like a pure accident,[00:11:52] Alex Volkov: it's oh, oops. You're going through a mixer. I think, a responsible So acknowledgement, that this kind of happened to you is also important.[00:11:58] I saw LDJ from news research can acknowledge that. Because many of these datasets are collections of other datasets. There's a bunch of people are baking, basically. It's alchemy. Right. And so sometimes you don't know. Sometimes you pull an open source dataset and they announce, oh, you know what, actually, the MMLU benchmark which we used to Specifically identify models that did go into this data set, that then went into that data set.[00:12:22] So sometimes it's actually an accident and folks take it down. But I've seen some competitive folks who want to put their name out there because people are starting to notice which is the top[00:12:30] swyx: model. For those who want a fun take on this so the file one dataset. FindOne model from Microsoft was accused of being contaminated.[00:12:37] And I saw this joke paper that was fantastic. It was called, training on the test set is all you need. It's a super small model that just memorizes everything. It was fantastic. So yeah, contamination, I think we've actually covered it in a previous episode before. So we're good. But again, I want to give people a map into the open source AI model, the universe.[00:12:57] And Alex, you can also jump in here because you guys have spent a lot more time with them than I have. So, what should people know about Technium? What should people know about Noose? And then we can go down the list. Yeah,[00:13:05] Wing Lian: I think so. I think if we start with, Technium. When you talk to him, he's gonna say, I think, I think his response is that he wants to build GP4 on his laptop, right?[00:13:14] So, very, very good at building general models. I think with Noose, Noose Research, they're looking at more, sort of, More, more research focused things, like their Yarn models, I don't, I don't, they didn't actually train their, they have their own trainer for their Yarn models, but So they did not use Xlato for that one?[00:13:30] They didn't use that, but like Is that, you don't have support for it? I think we do support Yarn, I think, I'd have to double check that answer. Yeah, I'm just kind of curious what you can and cannot support, and Yeah, I mean, Yarn is supportable, it's basically, I think it's just replacing, I think, the rope part of that, so Yeah, not, not a big deal.[00:13:48] Yeah, it's not a big deal, it's just I haven't gotten to it, not enough people have asked, I think a lot of people have asked for other things, so it's just, squeaky wheel, right? I think at the end of the day, people are like building these data sets and I think if you sort of map things chronologically, these make more sense because it's like, how do we incrementally improve all of these models?[00:14:07] So a lot of these models are just incremental improvements over the last thing, right? Whether it is sort of through methods of how do we, how did we curate the data set? How did we improve the quality of the data set? So, you maybe LDJ talked about it right on I think for, for Capybara and Puffin, like how those, those were very specific dataset curation techniques that he works on.[00:14:29] The Case for Open Source AI[00:14:29] Alex Volkov: So there's, folks are doing this for dataset curation. Folks are doing this for skillset building as well. Definitely people understand that open source is like very important, especially after the, the, the, the, the march, the debacle, the OpenAI weekend that we all had. And people started noticing that even after developer day in OpenAI, the APIs went out.[00:14:48] And then after that, the whole leadership of the company is swiftly changed and people, there was worries about, you know. How can people continue building AI products based on these like shaky grounds that turned attention definitely to Technium at least in open RMS I started seeing this more and more on Twitter, but also other models and many companies They're gonna start with open AI just to get there quick, and then they they think about okay Maybe I don't want to share my knowledge.[00:15:13] Maybe I don't want to sign up for Microsoft. Maybe they will change their terms and conditions so What else is out there? They turned to other companies. Up until yesterday, Google was nowhere to be found. We've talked about Gemini a little bit before in a previous And you can tune in[00:15:26] swyx: to[00:15:26] Alex Volkov: Thursday Eye.[00:15:26] Yeah, you can tune in to Thursday Eye. We covered the Gemini release a little bit. And but many are turning into the open source community and seeing that Meta released and continues to release and commit to open source AI. Mistral came out and the model is way smaller than LLAMA and performs Significantly better.[00:15:43] People play with OpenRMS, which is currently techniums based, news researched, sourced, axolotl trained OpenRMS, I assume, right? And then they play with this and they see that, okay, this is like GPT 3. 5 quality. We had GPT 4. 5 birthday just a week ago. A week ago, a year ago, a week ago, we never, interacted with these models of this caliber.[00:16:04] And now there's one open source, one that's on my laptop, completely offline, that, I can continue improving for my use cases. So enterprises, companies are also noticing this. And the open source community folks are building the skill set, not only the data sets. They're building the actual kind of, here's how we're going to do this, with Axelotl, with these data sets.[00:16:21] The curation pieces. Now. Interesting. There's like recipes of curation. The actual model training is kind of a competitive thing where people go and compete on these leaderboards that we talked about, the LMC arena, and that recently added open air and recently added open chat and a bunch of other stuff that are super cool.[00:16:37] The hug and face open source leaderboard. And so there's a competitive aspect to this. There's the open source. Aspect to this, like Technium says, I want GPT 4 on my laptop. There's the, let me build a skill set that potentially turns into a company, like we saw with Noose. Noose just, started organizing, a bunch of people on Discord, and suddenly, they're announcing their company.[00:16:54] It's happening across all these modalities, and suddenly all these people who saw these green pastures and a fairly quick way to, hey, here's a cool online community I can, start doing cool stuff with. You mentioned the same in the beginning, right? Like, after your accident, what's cool, let me try this out.[00:17:08] Suddenly I start noticing that there's a significant movement of interest in enterprising companies into these areas. And, this skill set, these data sets, and this community is now very Very important, important enough to create an event which pulls in Andrei Karpathy from OpenAI to come and see what's new Jeremy Howard, like the event that we just talked about, people are flying over and this is just a meetup.[00:17:28] So, definitely, the community is buzzing right now and I think Axelot is a big piece as well.[00:17:34] Orca and OpenOrca[00:17:34] Wing Lian: Cool. Maybe we can talk about like Orca real quick, Orca, OpenOrca rather, I think there was a lot of buzz when, the first Orca paper came out. And just briefly, what is Orca? Yeah, Orca was basically having traces of like chain of thought reasoning, right?[00:17:48] So they go and they, they distill sort of GPT 4. They take, they take a sampling of data from the Flan dataset. Maybe we can like add some show notes in the Flan dataset. Yeah, but we've covered it. Okay, cool. Use GPT 4 to say, all right, explain this in a step by step reasoning, right?[00:18:06] And then you take that and you, they train the model and it showed, very good improvements across a lot of benchmarks. So OpenOrca was sort of the open reproduction of that since Microsoft Research never released that particular data set. And going back to sort of the Hugging Face leaderboard thing, those models did really well.[00:18:23] And then I think, so sort of the follow up to that was SlimOrca, right? I think Going into and building the OpenOrca dataset, we never really went in and, validated the actual answers that GPT 4 gave us, so what we did was one from OpenChat actually cross referenced the original Flan, the original Flan response, the human responses, the correct answers with the dataset, and then I went and took it and sent all of, both of them to GPT 4 and said, is this answer mostly correct, right?[00:18:54] Yeah. And then we were able to filter the dataset from, At least of the GPT 4 only answers from like 800, 000 to like 500, 000 answers or rows and then, and then retrain the model and it had the same performance as the original model to within I think, 0. 1 percent here about, and 30 percent less data.[00:19:13] So, yeah. Okay.[00:19:15] swyx: Interesting. So, I mean, there's, there's so much there that I want to highlight, but yeah. Orca is interesting. I do want people to know about it. Putting chain of thought into the data set like it's just makes a ton of sense one thing I think it would be helpful for people to scope thing these things out is how much data are we talking about when when you When people are fine tuning and then how much time or resources or money does it take to train to fine[00:19:36] Wing Lian: tune?[00:19:37] Yeah, so I think there's a little bit of overlap there with sort of like fine tuning techniques, but let's say Orca and I think even Hermes, they're both relatively large data sets like 10 billion tokens. Yeah. So large data sets being or the original Orca was, or the original open Orca was 800,000 rows.[00:19:55] I believe it was somewhere in the ballpark of like a gigabyte of data, of gigabyte, of text data. And I, I don't. I believe, Hermes was, is like a quarter million rows of data, I don't know the actual byte size on that particular one. So, going and training a, let's, let's say everybody's training 7 billion Mistral right now, right?[00:20:15] So, to tri I, I believe to fine tune 7 billion Mistral on, let's say, 8 A6000s, which have 48 gigabytes of VRAM, I believe, It takes about 40 hours, so 40, and then that's, depending on where you get your compute, 40 times 6, so it's like 500 to fine tune that model, so, and, and that's assuming you get it right the first time, right?[00:20:44] So, you know.[00:20:45] swyx: Is, is that something that X. Lotto handles, like, getting it right the first[00:20:48] Wing Lian: time? If you talk to anybody, it's like you've probably tried at least three or four runs or experiments to like find the right hyperparameters. And after a while you sort of have a feel for like which, where you need your hyperparameters to be.[00:21:04] Usually you might do like a partial training run, do some benchmark. So I guess for Al Farouk, whether you're going by his. This is Jeremy, he's, his actual name, or his twitter handle. He released the Dharma dataset, which is basically a subset of all the benchmarks. And Axolotl actually supports, you know taking that subset and then just running many benchmarks across your model every time you're doing an evaluation so you can sort of like see sort of relative it's not going to be the actual benchmark score, but you can get ideas alright, is this benchmark improving, is this benchmark decreasing, based on, you know Wait,[00:21:39] swyx: why don't you run the full benchmark?[00:21:41] What, what, what The[00:21:42] Wing Lian: full benchmarks take Take a long time. Significant, yeah, significant amount of time. Yeah. And Okay, so that's like[00:21:48] swyx: mini MMLU. Yeah. Like,[00:21:49] Wing Lian: mini BigBench or whatever. Yep, exactly.[00:21:51] Alex Volkov: It's really cool. We, when I joined Web2Masters just recently, and one of the things that I try to do is hey I'm not, I'm a software engineer by trade, I don't have an MLE background, But I joined a company that does primarily MLE, and I wanted to learn from the community, Because a lot of the open source community, they use weights and biases, And the benchmark that you said that Pharrell did, remind me of the name, sorry.[00:22:13] Dharma? Dharma, yeah, yeah. So Luigi showed me how Dharma shows inside the dashboard. In Wi and Biases dashboard and so you can actually kinda see the trending run and then you can see per each kind of iteration or, or epoch or you can see the model improving trending so you can on top of everything else.[00:22:29] The wi and biases gives like hyper parameter tracking, which like you, you started with common line and that's really hard to like remember. Also the Dharma data set, like the quick, the mini orca mini, you mini many different things. It's pretty cool to like visualize them as well. And I, I heard that he's working on a new version of, of Dharma, so Dharma 2, et cetera.[00:22:47] So hopefully, hopefully we'll see that soon, but definitely it's hard, right? You start this training around, it said like 40, 50 hours. Sometimes, sometimes it's like your SSHing into this machine. You, you start a process, you send it with God and you just go about your day, collecting data sets, and then you have to return.[00:23:04] And the whole process of instrumentation of this is still a little bit like squeaky but definitely. Tuning performance, or like grabbing performance in the middle of this, like with Dharma and some other tools, is very helpful to know that you're not wasting precious resources going somewhere you shouldn't go.[00:23:21] Yeah.[00:23:22] swyx: Yeah. Very cool. Maybe I'll, I'll, before we go into like sort of more details on fine tuning stuff, I just wanted to round out the rest of the Excel autoverse. There's, there's still Eric Hartford stuff. I don't know if you want to talk about Pygmalion, Disco, anything that you know about[00:23:35] Wing Lian: those, those things.[00:23:36] DiscoLM and Model Stacking[00:23:36] Wing Lian: Yeah, I think like one of the, definitely one of the more interesting ones was like the Disco 120b, right? Yeah, I know nothing about it. Yeah. So, so. Alpen from Pygmalion AI, right, so they, so Pygmalion is a sort of a, it's, it's, they have their own community, a lot of it is based around, roleplay models, those sorts of things, and Alpen, like, put together, merged together Llama270B, so, and Alpen, like, put together, merged together Llama270B, so, I don't remember how he stacked them together, whether he merged the layers in between. There's a whole, there's a whole toolkit for that by Charles Goddard, where you can like take a single model and like stack them together or multiple models merge.[00:24:18] That's like a whole other talk and a whole other tool set, but was able to create this 120. Billion parameter model out of a LAMA two 70 B. And then I believe the, yeah, disco is a fine tune of, of the, the, the sort of the base one 20 B is, I believe Goliath one 20 B. So, and, and what are the[00:24:37] swyx: headline results that people should know about[00:24:39] Wing Lian: disco?[00:24:39] I think for the headline results, I, I've, I haven't played with it personally because it's. It's a very large model and there's a lot of GPU, right? But, like, from what I've heard anecdotally, it performs really well. The responses are very good. Even with, like, just, even the base model is a lot better than, Llama70b.[00:24:57] So, and we, I think generally everybody's like, we would all love to fine tune Llama70b, but it's just, it's so much, it's so much memory, so much compute, right?[00:25:07] Datasets and Evals over Models[00:25:07] Wing Lian: I[00:25:07] Alex Volkov: want to touch on this point because the interesting thing That comes up out of being in this ecosphere and being friends with open source folks, tracking week to week state of the art performance on different models.[00:25:19] First of all, a lot of the stuff that the folks do a couple of weeks ago, and then something like Mistral comes out, and a lot of the stuff back then, Doesn't technically make sense anymore. Like the artifacts of that work, the actual artifacts, they don't no longer make sense. They're like lower on the on, on the hug and face leaderboard or lower on LM CS leaderboard.[00:25:36] But some of the techniques that people use, definitely the datasets. The datasets keep traveling, right? So open airmen, for example, is the dataset. The tum cleaned up for only. Open sourceable data that previously was just Hermes. And that, it was previously used to train Lama. And then once Mistral came out, it was used to train Mistral.[00:25:54] And then it became significantly better on the 7b base Mistral. So the data sets keep traveling, keep getting better a little bit here and there. And so the techniques improve as well. It looks like both things are simultaneously true. The artifacts of a month and a half ago. The, the actual models themselves, it's great the hug and face has them, because not every company can keep up with the next weeks', oh, I, I'll install this model instead, sell this model instead.[00:26:19] But the, the techniques and the, the dataset keep improving as we go further, and I think that's really cool. However, the outcome of this is that for a long time. For many, many people, including us, that we do this every week. We literally talk with people who release these models every week. It's really hard to know.[00:26:36] So, there's a few aspects of this. One, I think, like you said, the bigger model, the 70B models, you actually have to have somebody like Perplexity, for example, giving you access to the 70B really fast. Or you have to, like, Actually, find some compute, and it's expensive, especially for the bigger models. For example Falcon 180B came out, like the hugest open source model.[00:26:56] How do you evaluate this if you can't run it? Nobody liked it. It's really, so first of all, nobody liked it, but secondly, only the people who were able to find compute enough to run inference on this, they only had like, I can't run this on my laptop, and so that's why it's much easier, something like OpenRMS 7 to be, 7B, it's much easier, because you can run this on your MacBook.[00:27:14] It's much easier to evaluate. It's much easier to figure out the vibes, right? Everybody talks about the vibes as an evaluation check. If you're plugged in enough, if you follow the right people, if they say pretty much the same things all independently, then you run into a problem of whether they're repeating, and their stochastic parents are repeating the same thing, or they actually evaluated themselves.[00:27:31] Yeah, you never know. But, you never know, but like, I think on a large enough scale on Twitter, you start getting the feel. And we all know that like, OpenRMS is one of the top performing models, benchmarks, but also vibes. And I just wanted to highlight this vibes checks thing because you can have the benchmarks, you can have the evaluations, they potentially have contamination in them, potentially they not necessarily tell you the whole story because some models are good on benchmarks, but then you talk to them, they're not super helpful.[00:28:00] And I think it's a combination of the benchmarks, the leaderboards, the chatbot, because LMSys, remember, their ranking is not only based on benchmarks, it's also people playing with their arena stuff. People actually like humans, like, get two answers. I think they completely ignore benchmarks. Yeah, and then They only do ELO.[00:28:18] Oh, they do ELO completely, right? So that, for example, is just like people playing with both models and say, Hey, I prefer this one, I prefer that one. But also there's like some selection bias. The type of people who will go to LMCs to play with the models, they're a little bit specific in terms of like who they are.[00:28:33] It's very interesting. There's so many models. People are doing this in this way, that way. Some people are doing this for academic rigor only to test out new ideas. Some people are actually doing this like the Intel fine tunes of Mistral. Intel wanted to come out and show that their hardware approach is possible, Mistral, etc.[00:28:51] And it's really hard to know, like, what to pick, what to use. And especially on the bigger models, like you said, like the Llama 70B, the Falcon 180B. It's really because, like, who has the compute to validate those? So I would mention that, like, use with caution. Like, go and research and see if the biggest model that just released was actually worth the tokens and the money you spend on it.[00:29:12] To try and, if you're a business, to integrate it.[00:29:15] Distilling from GPT4[00:29:15] swyx: Since you said use of caution, I'll bring in one issue that has always been in the back of my mind whenever I look at the entire universe of open source AI models, which is that 95 percent of the data is derived from GPC 4, correct?[00:29:30] Which technically you can't use for commercial licenses,[00:29:34] Wing Lian: right?[00:29:35] swyx: What is the community's stance on this kind of stuff?[00:29:40] Wing Lian: I think from the community stance, like I feel like a lot of us are just experimenting, so for us, it's like, we're not going and building a product that we're trying to sell, right?[00:29:49] We're just building a product because we think it's interesting and we want to use it in our day to day lives, whether or not we try and integrate it. Personal use, yeah. Yeah, personal use, so like, as long as we're not selling it, yeah, it's fine. But[00:30:01] swyx: like, I as a company cannot just take OpenHermes and start serving[00:30:05] Alex Volkov: it and make money on it.[00:30:06] OpenHermes you can. Because the opening of OpenHermes, I think, is a clean up. That did after the regular Hermes, please folks, check your licenses before you listen to podcasts and say, Hey, I will tell you though, you could say the same thing about OpenAI. You could say the same thing kind of makes sense, where OpenAI or StabilityAI trains their diffusion model on a bunch of pictures on the internet, and then the court kind of doesn't strike down Sarah Silverman, I think, or somebody else, who came and said, hey, this has my work in it, because of the way how it processes, and the model eventually builds this knowledge into the model, and then it doesn't actually reproduce one to one what happened in the dataset.[00:30:45] You could claim the same thing for open source. Like, we're using And by we, I mean the, the open source community that I like happily report on uses GPT 4 to rank, for example, which is the better answer you, you, that's how you build one, one type of data set, right? Or DPO or something like this, you, you basically generate data set of like a question and four answers, for example, and then you go to GPT 4 and say, Hey, smartest model in the world right now, up to Gemini Ultra, that we should mention as well.[00:31:11] Which one of those choices is better? But the choices themselves are not necessarily written with GPT 4. Some of them may be, so there's like full syntactic datasets. But there's also, datasets are just ranked with GPT 4. But they're actually generated with a sillier model, or like the less important model.[00:31:25] The lines are very blurry as to what type of stuff is possible or not possible. And again, when you use this model that's up on Hug Face, the license says you can use this. OpenAI is not going to come after you, the user. If anything, OpenAI will try to say, hey, let's prevent this, this type of thing happening, and the brain, but I honestly don't think that they could know even, not that it makes it okay, it's just like, They also kind of do this with the Internet's archive, and also, I think that some of it is for use.[00:31:55] You use models to help you augment tasks, which is what GPT 4 lets you do.[00:32:00] swyx: Yeah, the worst thing that OpenAI can do is just kick you off OpenAI. That's because it's only enforced in the terms of service.[00:32:05] Alex Volkov: Sure, but just like to make sure, to clarify who they're going to kick out, they could kick out like News, for example, if news are abusing their service, a user of the open source, fully Apache 2 open source, for example, They won't get kicked out if they use both, just because they use both.[00:32:22] I don't believe so. I don't think OpenAI has a claim for that.[00:32:25] swyx: Well, we're not lawyers, but I just want to mention it for people to know it's an issue.[00:32:30] Wing Lian: And one of the things, like, I talked to someone recently, and I think that they also are like interested in it, but also to the point of like, right, if I use a model trained on data, using GPT for data, But I use that model to then regenerate new data.[00:32:46] Is that model, is that data okay? So like you start going down this whole rabbit hole. So yeah. All right.[00:32:53] swyx: Fantastic. Cool. Well, I think that's roughly highlights most of the open source universe. You also have your own models. Do you want to shout out any one of them? Yeah.[00:33:01] Wing Lian: I mean, I think like, I think Early on, Manicore got a lot of love.[00:33:04] I think it was mostly popular in, like, the roleplay communities. It was, it tended to be pretty truthful. It tended to be, like, have relatively good answers, depending on who you ask, right? But, I think for me, it was just, Releasing models was a way to try and, like, continue to build out the product, figure out what I needed to put into the product, how do I make it faster, and, if you've got to, like, go and debug your product, you may as well have it do something useful.[00:33:29] Awesome. So, yeah.[00:33:31] Finetuning - LoRA, QLoRA, ReLoRA, GPTQ[00:33:31] swyx: Okay, and then maybe we'll talk about just fine tuning techniques. So this is going to be a little bit more technical than just talking about model names and datasets. So we started off talking about LoRa, QLoRa. I just learned from your readme there's ReLoRa. Which I've never heard about.[00:33:45] Could you maybe talk about, like, just parameter efficient fine tuning that whole, that[00:33:50] Wing Lian: whole journey, like, what people should know. Yeah, so with parameter efficient fine tuning, I think the popular ones, again, being, let's, we'll start with lore, right? So, usually what you do is you freeze all the layers on your base, on the base model, and then you, at the same time, you sort of introduce additional Oh, this is tight.[00:34:08] No. You introduce, another set of layers over it, and then you train those, and it is done in a way that is mathematically possible, particularly with LORs that you can, then you, you, When you, when you train the model, you, you run your inputs through the base model, whose weights are frozen, but you, then you also run it through the additional weights, and then at the end you combine the weights, and then, and then, or you combine the weights to get your outputs, and then at the end, and when you're done training, you're left with this other set of weights, right, that are completely independent, and And then from that, what you can do is, some person smarter than I figured out, well, oh, they've done it in such a way that now I can merge these weights back into the original model without changing the architecture of the model, right?[00:35:03] So, so, that tends to be, like, the go to, and You're training much fewer parameters so that when you do that, yes, you still need to have all of the original weights, but you have a smaller gradient, you have a smaller optimizer state, and you're just training less weights, so you can tend to train those models on, like, much smaller GPUs.[00:35:27] swyx: Yeah. And it's roughly like, what I've seen, what I've seen out there is roughly like 1 percent the number of parameters that you're trading. Yeah, that sounds about right. Which is that much cheaper. So Axelotl supports full fine tune, LoRa, QLoRa,[00:35:40] Wing Lian: Q. Yes. So, so QLoRa is, is very similar to LoRa. The paper was, if I remember correctly, the paper was Rather, traditionally, most people who did Loras were, were, they were quant, they were putting the model weights in 8 bit, and then fine tune, parameter efficient fine tuning over the Lora weights, and then with QLora, they were quantizing all of those, they were then quantizing the weights down to 4 bit, right, and then I believe they were also training on all of the linear layers in the model.[00:36:15] And then with ReLore, that was an interesting paper, and then, I think, like, it got implemented. Some people in the community tried it, tried it out, and it showed that it didn't really have the impact that the paper indicated that it would. And from what I was told recently, that they re I guess they re released something for Relora, like, a few weeks ago, and that it's possibly better.[00:36:44] I personally haven't had the time. What was the[00:36:46] swyx: main difference,[00:36:47] Wing Lian: apart from quantization? I don't know. Okay. What was the main difference, sorry?[00:36:49] swyx: Apart from quantization, right? Like,[00:36:50] Wing Lian: Qlora's thing was, like, we'll just drop off some bits. With Relora, what they did was, you would go through, you would define some number of steps that you would train, like, your Lora with, or your Qlora.[00:37:01] Like, you could do Like, ReqLore, if you really wanted to, you would, you would train your LoRa for some number of steps, And then you would merge those weights into your base model, and then you would start over. So by starting, so, then by starting over, The optimizer has to find, like, sort of, re optimize again, and find what's the best direction to move in, and then do it all again, and then merge it in, do it all again, and theoretically, according to the paper, doing ReLore, you can do parameter efficient fine tuning, but still have sort of, like, the performance gains of doing a full fine tuning, so.[00:37:38] swyx: Yeah, and[00:37:39] Wing Lian: GPTQ? And GPTQ, so it's, I think with GPTQ, it's very similar to, more similar to QLore, where you're, it's mostly a quantization of the weights down to like 4 bit, where GPTQ is a very, is a specific methodology or implementation of quantization, so. Got it.[00:37:57] Alex Volkov: Wang, for, for folks who use Axolotl, your users, some people who maybe, Want to try it out?[00:38:03] And do they need to know the differences? Do they need to know the implementation details of QLora versus ReLora? Or is it okay for them to just know that Axolotl is the place that already integrated them? And if that's true, if that's all they need to know, how do they choose which method to use? Yeah,[00:38:22] Wing Lian: so I think like, I think most people aren't going to be using ReLora.[00:38:25] I think most people are going to be using either Lora or QLora. And I think they should have it. They should have an understanding of why they might want to use one over the other. Most people will say that with Qlora, the quality of the final model is not quite as good as like if you were to do a LoRa or a full fine tune, right?[00:38:44] Just because, you've quantized these down, so your accuracy is probably a little off, and so that by the time you've done the Qlora, you're not moving the weights how you would on a full fine tune with the full parameter weights.[00:38:56] Interesting.[00:38:57] swyx: Okay, cool. For people who are more interested, obviously, read the papers. I just wanted to give people, like, a high level overview of what these things are. And you've done people a service by making it easy for people to try it out. I'm going to, I'm going to also ask a question which I know to be wrong, but I'm curious because I get asked this all the time.[00:39:15] What is the difference between all these kinds of fine tunes[00:39:17] Wing Lian: and RLHF? Okay, between all of these sorts of fine tunes and RLHF. So all of these sorts of fine tunes are based, are, ideally, this, they are taking knowledge that the base model already knows about, and presenting it in a way to the model that you're having the model answer like, Use what it already knows to sort of answer in a particular way, whether it's, you're extracting general knowledge, a particular task, right?[00:39:44] Instruct, tune, chat, those sorts of things. And then generally with RLHF, so what is, let's go back, what is it? Reinforcement Learning with Human Feedback. So if we start with the human feedback part, What you're doing is you generally have, you have like a given prompt and then you, maybe you have one, maybe you have two, I think, like if you look at with Starling, you have like up to what, seven different, seven different possible responses, and you're sort of ranking those responses on, on some sort of metric, right, whether the metric is how much I, I might like that answer versus or I think with like starling is like how how how helpful was the answer how accurate was the answer how toxic was the answer those sorts of things on some sort of scale right and then using that to go back and like sort of Take a model and nudge it in the direction of giving that feedback, to be able to answer questions based on those preferences.[00:40:42] swyx: Yeah, so you can apply, and is it commutative? Can you apply fine tuning after and onto an RLHF model? Or should the RLHF apply, come in afterwards,[00:40:54] Wing Lian: after the fine tune? Um, I, yeah, I don't know that there's There's been enough research for one way or another, like, I don't know.[00:41:02] That's a question that's been asked on Discord. Yeah, like, I definitely would say I don't know the answer. Go and try it and report back to me and let me know so I can answer for the next guy.[00:41:10] swyx: It's shocking how much is still unknown about all these things. Well, I mean, that's what research is for, right?[00:41:16] Wing Lian: So actually I, I think I saw on the top of a leaderboard, it was a, it was a mytral base model, and they didn't actually fine tune it. They, or they, they just did RLH, they did like an RLHF fine tune on it using like, I don't, I don't recall which dataset, but it was like, and it benchmarked really well.[00:41:37] But yeah, you'd have to go and look at it. But, so it is interesting, like going back to that, it's like. Traditionally, most people will fine tune the model and then do like a DPO, PPO, some sort of reinforcement learning over that, but that particular model was, it seemed like they skipped like the supervised fine tuning or Scott.[00:41:55] Axolotl vs HF Transformers[00:41:55] swyx: Cool. One thing I did also want to comment about is the overall, like, landscape, competitive landscape, I don't know. Hugging Face Transformers, I think, has a PFT module.[00:42:05] Wing Lian: Yeah, yeah, the PEFT, the Parameter Efficient Fine Tuning, yep. Is that a competitor to you? No, no, so we actually use it. We're just a wrapper over sort of, sort of the HuggingFace stuff.[00:42:15] So, so that is their own sort of module where They have, taken the responsibility or yeah, the responsibility of like where you're doing these parameter efficient fine tuning methods and just sort of like, it is in that particular package where transformers is mostly responsible for sort of like the modeling code and, and the trainer, right.[00:42:35] And then sort of, there's an integration between the two and, there's like a variety of other fine tuning packages, I think like TRL, TRLX, that's the stability AI one. Yeah, I think TRL likes the stability, yeah, Carper, and TRL is a hugging face trainer. Even that one's just another wrapper over, over the transformers library and the path library, right?[00:43:00] But what we do is we have taken sort of those, yes, we've We also use that, but we also have more validation, right? So, there are some of us who have done enough fine tunes where like, Oh, this and this just don't go together, right? But most people don't know that, so like Example?[00:43:19] Like, people want to One and one doesn't go together. I don't have an example offhand, but if you turn this knob and this knob, right? You would think, all right, maybe this will work, but you don't know until you try. And then by the time you find out it doesn't work, it's like maybe five minutes later, it's failed.[00:43:34] It's failed in the middle of training or it's failed during the evaluation step. And you're like, ah, so we've, we've added a lot of, we've added a lot more validation in it. So that like, when you've, you've created your configuration, you run it through and now you say. The validation code says this is probably not right or probably not what you don't, not what you want.[00:43:52] So are you like a, you[00:43:53] swyx: do some linting of your YAML file?[00:43:56] Wing Lian: There, I guess you could call it linting, it's sort of like Is there a set of rules out[00:44:00] swyx: there somewhere? Yeah, there's a set of rules in there. That's amazing, you should write documentation like This rule is because, this user at this time, like, ran into this bug and that's what we invested in.[00:44:10] It's like a good collection[00:44:11] Wing Lian: of knowledge. Yeah, it is, and I guess like, if you really wanted to, like, figure it out, I guess you could, like, git blame everything, and But, yeah, it's, so, I think that's always a useful thing, it's like Because people want to experiment but they don't, people will get frustrated when you've experiment, you're experimenting and it breaks and you don't know why or you know why and you've just gone down the rabbit hole, right?[00:44:37] So, so I think that's one of the big features that's, that I think I find important because it's It prevents you from doing things you probably shouldn't have, and it, and sometimes we will let you do those things, but we'll try and warn, warn you that you've done that.[00:44:50] I[00:44:51] Alex Volkov: have a follow up question on this, actually, because yesterday we hung out to this open source event, and I spent time by you a couple times, like when people told you, oh, XLR, I use XLR, it's super cool, and then the first thing you asked is, like, immediately, like, what can we improve?[00:45:04] And yes, from multiple folks, and I think we talked about this a little bit, where there's It's a developer tool. It's like a machine learning slash developer tool. Your purpose in this is to help and keep people, as much as possible, like, Hey, here's the best set of things that you can use right now. The bear libraries are, or the bear trainer, for example, is a bear trainer.[00:45:28] And also, maybe we should talk about how fast you're implementing these things. So you mentioned the first implementation took a week or so. Now there's a core maintainer group, right? There's like, features are landing, like Qlora, for example. Neftune, I don't know if that's one example of something that people potentially said that it's going to be cool, and then eventually, like, one of those things that didn't really shake out, like, people quickly tested this out.[00:45:48] So, there's a ton of Wait, Neftune is cancelled? I don't know if it's fully canceled, but based on vibes, I heard that it's not that great. So like, but the whole point that I'm trying to make with Neftune as well is that being existing in the community of like XLR or like, I don't know, even following the, the GitHub options or following the Discord, it's a fairly good way to like, learn these, Kind of gut feelings that you just, you just said, right?[00:46:14] Like where this, maybe this knob, that knob doesn't work. Some of these are not written down. Some of these are like tribal knowledge that passes from place to place. Axel is like a great collection of many of them. And so, do you get That back also from community of folks who just use, like, how do you know who uses this?[00:46:30] I think that's still an issue, like, knowing if they trained with XLR or should they add this to things? Talk about, how do you get feedback and how else you should get feedback?[00:46:38] Wing Lian: Yeah, I mean, most of the feedback comes from the Discord, so people come in and , they don't get a training running, they run into, like, obscure errors or, errors that That's a lot of things that maybe, maybe as a product we could catch, but like, there's a lot of things that at some point we need to go and do and it's just on the list somewhere.[00:46:58] Right that's why when people come up, I'm like, what, what were your pain points? Because like, as a developer tool, if you're not happy with it, or you come in and in the first, Takes you 30 minutes and you're still not happy. You leave the tool and you may, you might move on maybe to a better tool, maybe to, one with less frustration, but it may not be as good, right?[00:47:17] So I'm trying to like, figure out, all right, how can I reduce all this frustration? Because like for me, I use it every day for the most part, right? And so I am blind to that, right? Mm-Hmm. . Mm-Hmm. . I just know, I, I go do this, this, and this. It pretty much mostly works, right? But, so I don't have sort of that, alright, that learning curve that other people are seeing and don't understand their pain points.[00:47:40] Yeah,[00:47:40] Alex Volkov: you don't have the The ability to onboard yourself as a new user completely new to the whole paradigm to like get into the doors of like, Oh, no, I don't even know how to like ask about this problem or error.[00:47:53] swyx: Cool. The last few things I wanted to cover was also just the more advanced stuff that you covered yesterday.[00:48:00] 20x efficiency with StackLlama and Multipack[00:48:00] swyx: So I'll just, caution this as like, yeah, this is more advanced. But you mentioned Stackllama and Multipack. What are they[00:48:06] Wing Lian: and what should people know? Yeah, so, so, Stack Llama was, that paper came out, so Stack Llama I think was like, two, two, two separate, two separate concepts that they announced, so the first one was They being hugging face.[00:48:20] Yeah, sorry, yes, they being hugging face, so the first one being sort of like, this idea of packing, like some packing sequences together, so like, if we think about training data, right, your training data is, let's say, to keep the math easy, let's say your training data is 500, We, we, we, we will use the terminology words.[00:48:39] Let's say your training data is 500 words long, and let's say your, your context length, you know how much data your, that your model can accept is like, or that you want feed into your model. It's, let's say, we won't use tokens again, we'll we'll use it is it's 4,000 tokens, right? So if you're training at 4K Con or four 4,000 4K contacts and you're only using 500 of it, you're sitting like with the other 1500.[00:49:05] 3, 500 words that you're not using, right? And typically that's either filled with these PAD tokens, so I think I made the analogy last night that it's like having sort of like a glass here you fill it up with a shot of liquor and then you're and that's your training data and then you just fill it up with more water and those are your PAD tokens and it's just, it doesn't do much, right?[00:49:27] It's still the same thing, but you still have to go through all of that to go through all your training data. And then, so what Stack Llama showed was you could just sort of take your training data, append the next row of training data until you filled that entire 4k context, so in this example, right, with 500 words to 4k, that's 8 rows of training data.[00:49:48] But, the problem with that is, is that with a lot of these transformer models, they're very much relying on attention, right? So, like, if you now have this sequence of words that now, in order for the, the model has seen all of these other words before, right? And then it sees another set of words, another set of words, but it's learning everything in context of all the words that it's seen before.[00:50:13] We haven't corrected the attention for that. And just real quickly, since I said that that paper was two concepts, the other one was, I believe it was like a reinforcement learning, but outside the scope of this. So going from that, I implemented that early on because I was like, Oh, wow, this is really great.[00:50:29] And. Yes, because it saves you a bunch of time, but the trade off is a little bit of accuracy, ultimately, but it still did pretty well. I think when I did Manicore, I think it used sort of that concept from Stack Llama of just sort of appending these sequences together, right? And then sort of the next evolution of that is Multipack, right?[00:50:51] So, there was a separate paper on that, it was, I believe it was referenced, it got referenced in the Orca paper, where you could, you could properly mask those out using like a, I think it was like a lower block triangular attention mask, and then sort of, so, So, there's that. I did try implementing that, manually recreating that mask, but then one from the OpenChat, so he was helping with OpenOrca as well, and he had done an implementation of Multipack, and where he used FlashAttention, so FlashAttention So that was released by TreeDAO, and it was this huge performance gain.[00:51:35] Everybody uses it now, even the Transformers library now, they've taken all of these, like, people are taking all of these models and sort of like, making it compatible with FlashAttention. But in Flash Tension, there is one particular implementation that lets you say, Well, I'm sending you all of these sequences like you would in Stack Llama, But let me send you another, another, Set of information about, this is where this set of sequences is, this is where the second set of sequences is.[00:52:06] So like, if it was like, 500 words long, and you stacked them all together, you would just send it a row of information that was like, 0, 500, 1000, 1500, etc, etc, out to 4000. And it would know, alright, I need to break this up, and then run the forward pass with it. And then it would be able to, and it was much more, much more performant.[00:52:29] And I think you end up seeing like 10x, 20x improvements over sort of, I mean, I think FlashAttention was like a 2x improvement, and then adding that with the Multipack, you start to see like, depending on, how much data you have, up to like a 20x improvement sometimes. 20x. 20x. Wow. Yeah.[00:52:48] And I only know the 20x because I, like, before last night, I was like, I re ran the alpaca, I looked up the alpaca paper because it was like, I just need a frame of reference where somebody did it, and I think they used eight A100s for three hours, and they said it cost them 100. I don't, I don't think eight A100s cost, I don't know how much it costs right now.[00:53:14] But I ended up rerunning it. Usually a dollar an hour, right? Yeah, so eight. The cheapest is like a[00:53:18] Alex Volkov: dollar, a dollar an hour for one.[00:53:20] Wing Lian: Yeah, so that's still like 24, 25. But maybe if you're going on Azure, maybe it's like, maybe it's 100 on Azure. I mean, it used to be more expensive, like, a year ago.[00:53:31] Yeah, and then, so I re ran it with sort of like, I turned on all of the optimizations just to see what it would be. And like, and usually Multipack is the biggest optimization, so Multipack with Flash Detention. And it, I think I spun it up on 8 L40s, and it ran, and I didn't let it run all the way through, I just grabbed the time, the estimated completion time, and it was like 30 minutes, so it would have cost like 4 or 5 to run the entire, like, reproduce the alpaca paper, right?[00:54:00] Which is crazy. It's crazy. 20x,[00:54:02] Alex Volkov: yeah. I want to ask about, like, you said you turned on all the optimization. Is that the yaml file with xlodl, you just go and like check off, like, I want this, I want that? Yeah, yeah,[00:54:10] Wing Lian: so there's like one particular yaml file in there, That, there's one particular YAML file in there that's like, it's under examples, llama2, fft, optimize.[00:54:20] So, I think someone had created one where they just turned, they put in all of the optimizations and turned them on. I mean, it actually, it does run, which is like, sort of surprising sometimes, because sometimes, you optimize this, optimize this, and sometimes they just don't work together, but, yeah.[00:54:36] Just turn the knobs on, and like, fine tuning should really just be that easy, right? I just want to flip the knob and move on with my life and not figure out how to implement it.[00:54:47] Tri Dao and Mamba[00:54:47] Alex Volkov: Specifically, the guy behind FlashAttention came up with something new. You want to talk about this a little bit? You want to briefly cover Mamba?[00:54:53] Yeah, let's talk about Mamba. Let's talk about Mamba. So, what is Mamba?[00:54:57] Wing Lian: Oh, gosh. I

This episode was recorded on June 25th, 2023 at the Culture Center Theater in Charleston, WV. The lineup includes John Pizzarelli, Maria Muldaur, Jennifer Hartswick Band, Melissa Carper, and Gabriel Royal. https://bit.ly/3QlGfDB

Discover the latest in Tesla's production, Senator Carper's financial moves, and the Airbnb short-term rental ban in NYC. Stay informed with #Tesla #SenatorCarper #NYCAirbnbBan Feel free to subscribe to us for more updates and information! We strive to provide engaging and informative content on various topics. Stay tuned for the latest news and insights.

  A magazine wrote earlier in the year that Fidlar is unapologetically back. The group took a noticeable three year hiatus right before the pandemic. They were burnt out after touring 10-11 years straight. But, what often gets misconstrued is that Fidlar planned the whole time to step away, which is far from the truth. Perhaps it's the mysterious move to delete everything on social media. But, the band had plans to release music without touring. Now, for the unapologetically back… bands often make a big deal about their return to the spotlight. That wasn't the case for Fidlar. Carper jokes “If anything, we are sorry we are back.” Fidlar released two covers in Nookie and Free Fallin' recently. The band is no strangers to covers after doing their own version of Sabotage early on in their career. There is no end in sight for Fidlar now. There will be endless “Don't Fuck With” EP volumes since they have so much music ready to go. This is an exciting interview because Carper was not afraid to open up. He did not shy away from talking about his issues with drugs and being in and out of juvie and rehab centers. He talked about the real reason he moved to California - leaving Hawaii behind. Having a flight booked for March 23 to Japan during the first year of the pandemic because he originally had plans of working with his cousin in Japan. Lastly, the Florida tour and his plans to do surprise pop ups in coffee shops. This was a really fun conversation. Fidlar is open to all kinds of press, including bad press, but my gut tells me the band will continue to receive positive reviews from here on out.

Connecting with your students this school year can be as simple as asking what's their favorite dipping sauce. In our 13-minute minisode, we welcome back North Carolina State Teacher of the Year Leah Carper as she shares her number one social and emotional learning strategy that has been successful with her Gen Z students. Plus she dives into programs that  support all students, including universal free lunch. Teachers in America profiles K–12 teachers across the country. Hear firsthand from the people who are shaping young lives in the classroom every day. If you or someone you know would be a good candidate for Teachers in America, please email us at shaped@hmhco.com.

Are there natural means of healing?With all the advancements in medicine and health diagnosis available to us today, it is still an insufficient solution to addressing the core issues of our health. The medications given to us only address the present situation but it does not help boost our immune system to fight off diseases in the long run.In this episode, Tayana encourages us to dive into a holistic health journey where she shares her belief that we have the power to heal ourselves in the most natural way.A life-long athlete, Tayana Carper, Co-Creator and Founder of What's Juicin, has always been passionate about educating and empowering others to take health into their own hands. Her journey as a division 1 basketball player at The College of the Holy Cross led her to a career in nutritional counseling and fitness training.Having experienced health issues in the past, became her motivation to find natural healing solutions through juicing herbs and superfoods. Her quest for better health not only helped her heal her own health issues but sparked the creation of What's Juicin', an award winning cold pressed juice delivery service in South Florida.Website: https://www.whatsjuicin.com/Recommended books: The Power of Now by Eckhart TolleInstagram: @whats_juicin***Co-host Graciela Laurent, is a published, award-winning and professionally certified portrait photographer specializing in Boudoir and Personal Branding. She create portraits of who you are and not just what you look like so that you can become who you've always been.Website: http://www.gracielalaurent.com/Co-host Julietta Wenzel, the Magical PT is the owner and founder of Body and Soul PT, as well as Soul Candy: intuitive, hand-made and one-of-a-kind jewelry and artwork. She supports people in finding the magic within themselves, creating balance in their body and soul.Websites: https://bodyandsoul-pt.com & https://soulcandy.love/***Voices of The Goddess with Julietta & Graciela is a podcast where we Empower, Inspire, and Uplift women to be the goddesses they truly are.Join us each week as we sit down for a heart to heart chat, sharing stories and insights with listeners across the globe. Laughter and tears alike abound as we access ancient wisdom in modern times through unique and exciting storytelling - supporting you on your life's journey. If you want to feel more Empowered, Inspired & Uplifted you can find us here:https://www.votgpodcast.com/ https://www.instagram.com/voicesofthegoddess/ https://www.facebook.com/votgpodcast/ https://www.facebook.com/groups/thecircleofgoddesses https://www.youtube.com/VoicesoftheGoddess Shine bright and have a magical day!Julietta & Graciela

What else is there to say. https://about.me/ianlane/ https://www.youtube.com/@clinicalappraisal/videos https://www.buymeacoffee.com/ianalaneRN https://www.paypal.com/paypalme/clinicalappraisal

Legislation that would reauthorize the Diesel Emissions Reduction Act through fiscal 2029 was recently introduced in the Senate. Tom Carper (D-Del.), chairman of the Environment and Public Works Committee, is the bill's lead sponsor. He explained the legislation is designed to promote health benefits by improving air quality nationwide. Administered by the U.S. Environmental Protection Agency, the DERA program is backed by federal grants. “Since its implementation in 2005, the Diesel Emissions Reduction Act has been one of our nation's most cost-effective tools for reducing diesel emissions,” Carper said June 22.

The following political analysis is from Business-Industry Political Action Committee (BIPAC) Senior Political Analyst Jim Ellis.  BIPAC is an independent, bipartisan organization.  It is provided solely as a membership benefit to the organization's 200-plus member companies and trade associations.  The views and opinions expressed do not necessarily represent those of any particular member or organization.

Episode 51 features updates from Mike and Dave about what's going on in their lives followed by a discussion on the domino effect following Senator Carper's recent announcement and how the political landscape will change because of it.We close the episode with a "Game Show Draft" in honor of National Game Show day (today, June 1). Thank you for your continued support of the show, and enjoy this week's episode!

The following political analysis is from Business-Industry Political Action Committee (BIPAC) Senior Political Analyst Jim Ellis.  BIPAC is an independent, bipartisan organization.  It is provided solely as a membership benefit to the organization's 200-plus member companies and trade associations.  The views and opinions expressed do not necessarily represent those of any particular member or organization.

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For high school English teacher Leah Carper, a challenge from her Gen Z students transformed her teaching. Hear from Leah, the 2023 North Carolina State Teacher of the Year. She shares how her students inspired her to leverage technology and innovate her instruction. Listen to learn Leah's tips for the modern classroom!Teachers in America profiles K–12 teachers across the country. Hear firsthand from the people who are shaping young lives in the classroom every day. If you or someone you know would be a good candidate for Teachers in America, please email us at shaped@hmhco.com.

Raised in Arkansas, Melissa Carper got her start playing bass in her family band as a kid. Now in Texas, she plays a wide variety of retro Americana ranging from country and Texas swing to early jazz.

On this episode of After-Hours, we are joined by James Carper of Car Shop Karoshi. Karoshi is a drift team from Pennsylvania that has been blowing up over the last couple of years. They came out this past year with sick matching paint jobs and liveries. These cars really grabbed my attention at Final Bout East! James is the first member we had on but we expect to have the rest of the team on the podcast over time as well. Can't wait to see what they do this coming year!Thanks for listening! Please leave a review if you enjoyed this podcast.@jamescarper@carshopkaroshiCheck us out on other platforms:Youtube: /FactionMotorsportsInstagram: @factionmotorsportsFacebook: /factionmotorsportsTiktok: @factionmotorsports

This week, to kick-start our fifth season we call into an organic vegetable farm in Texas to chat with an upright bassist who also happens to be a former New Orleans ace street performer, and singer and songwriter, who sounds like she might have stepped out of a saloon in 1955 filled with the warm echoes of her heroes Hank Williams and Patsy Cline: Melissa Carper. Is there such thing as a “new nostalgia” movement happening under our noses in the Americana scene? I'm going to say there is, thanks to folks like Melissa. She's lived several lives as a working music maker in groups like Sad Daddy (“Daddy” being her beloved nickname), Buffalo Gals, and the Carper Family (her folks in Nebraska growing up had a roving band), before collecting her favorite vintage-tinted songs and breaking out with her whip-smart solo debut Daddy's Country Gold and then 2022's Ramblin' Soul, which she penned while working on that vegetable farm with her fiddle player/partner during the height of the pandemic. The latter record is a celebration of the small victories and tiny glories of taking your hard earned art onto the road, while also pausing to reflect on the important folks she lost recently, like her beloved pup. While Melissa gets a good chuckle about being called the “Hillbilly Holiday” with her high lilting voice and silky delivery, it's the impossible pleasure of hearing the lost music of pre-modern country, jazz and blues fronted by a proudly queer bassist lead-singer that almost seems like science fiction when you look at it deeply. Make “new nostalgia” a new genre! Or throw genre right out the window and just turn modern classics like “Makin' Memories” (one of my top songs of 2022) up nice and loud, however you listen these days. Support this podcast at — https://redcircle.com/the-show-on-the-road-with-z-lupetin1106/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

FolkScene speaks to Melissa Carper about her terrific new album "Ramblin' Soul" and more. Interviewed by Allen Larman. Produced by Peter Cutler. ©FolkScene. It is cool to share FolkScene recordings with your friends, but the reproduction of our programs for commercial purposes is illegal. FolkScene airs on Sunday evenings from 6 to 8 p.m.(PDT) at KPFK 90.7 Los Angeles and online. at www.kpfk.org.

Giving credit where credit is due. Many thanks to songwriter and musician Beth Chrisman for the (official) introduction to The Carper Family, back in the day. Your AMM host was quite taken by those superb three-part harmonies so beautifully delivered by Chrisman, Jenni Miori-Hodges and Melissa Carper. Only one Carper in this acoustic trio, mind […]

Help produce Basic Folk by contributing at https://basicfolk.com/donate/Upright bassist, singer and songwriter Melissa Carper has been playing in bands since she took up the position of bass in her family band at the age of 12. She grew up with a reverence for country music in her small town Nebraska family. The original Carper Family band toured regionally on the weekends at Elks lodges, VFWs and small bars. Little Melissa made $50 a gig, which allowed her to take her friends out for dinner and give her an early sense of what it was like to be a paid musician. She attended school for music, but ended up leaving two and a half years in and began her rambling.Melissa's lived in Nebraska, New York, Alaska, New Orleans, Arkansas and Austin to name only a few. She usually has stayed around a place for a couple years until she moves on. Along the way, she's formed many bands like a new version of The Carper Family, Sad Daddy and Buffalo Gals. In recent years, she's been releasing albums under her own name, which is strange because she does not like being the center of attention. Her writing is filled with humorous quips, even though she claims to have a “slow wit.” Her classic country sound is unique in that her writing is sharp, her delivery is relaxed and her voice is unreal. She spent a lot of time studying the voices of Hank Williams and Leadbelly to develop that honeyed, yet raw sound. Melissa Carper is the real deal! Go check out her new album Ramblin' Soul and enjoy our conversation.Advertising Inquiries: https://redcircle.com/brands

Richard hails from little falls Minnesota, Richard been in the business since the 80s

The sweet, sweet croon of “Ain’t A Day Goes By” is from the forthcoming release Ramblin’ Soul by Melissa Carper, which you’ve probably heard on KUTX recently. The new album is out Nov. 18, and from time to time, your AMM host brings out a few tunes from Carper’s 2021 release Daddy’s Country Gold, like […]

Welcome to this very, very special edition of the Fifth Wheel Podcast! We feature a double collab this week with F1 Tik Tok content creator Dawssss (@dawsFormula1) and Malcolm from the premier F1 betting account (@LightsOutF1Bets), giving us their insights into the Sport, as well as their predictions for the Singapore. As always, follow us on social media for exclusive content, and send in your predictions for the Singapore GP on our predictions poll, located on our link tree!

Only joking, just me waffling in with a bit of a 'day in the life of' episode!

An all around great angler, advocate of the sport and friend and member of the American Carp Society, Tim has been angling for carp for many years, specializing in targeting his beloved species from a boat. We take a look at his approach now and compare it to when he first started fishing for the species. Specimen Carp Angling in the USA is discussed in depth. An incredibly insightful Angler….don't miss this episode!

Sharing food is a powerful way to bring people together. Feast World Kitchen enables refugees and immigrants to serve their traditional recipes to local residents, who get to learn about—and enjoy—authentic, international cuisine without leaving town. This food business incubator is building bridges between cultures and knitting its local community together. Executive Director Ross Carper is partly responsible for making this idea a reality in Spokane, Washington. Listen to Ross' story and how God has uniquely called him to welcome the foreigner among us.