Podcasts about ssm

Join Mark Call of Shabbat Shalom Mesa fellowship for a two-part look at the second reading from the Book of Bemidbar, or Numbers, parsha "Naso" (Numbers 4:21 through all of chapter 7.) The Erev Shabbat reading begins with the 'head count' of the families which make up the tribe of Levi, through the process for the 'sota', or woman who is SUSPECTED of adultery, through the Nazerite vow, and then the longest, and most redundant, and thus 'perplexing' chapter in the Torah: https://hebrewnationonline.com/wp-content/uploads/2025/06/SSM-6-6-25-Naso-teaching-podcast-xx.mp3 Since Mark has talked about the 'cup' placed in the hand of the woman suspected of adultery often, and the connections, from Moses and the Golden Calf to Gethsemane and finally the Whore of Babylon in Revelation, this time the focus of the Sabbath Day midrash is a bit different. In John chapter 8, while Yahushua is teaching at the temple, a woman is brought before Him -- to 'test him' the text says -- who was allegedly caught in adultery, "the very act." Whereupon, Mark demonstrates, that most teachings in 'sun-day skool' proceed to miss the entire point of the story! And it certainly was NOT that He "did away with the law," or even "raised the bar," on His own Word. There is a larger pattern in evidence here as well. Naso: "Where is the MAN?" https://hebrewnationonline.com/wp-content/uploads/2025/06/WT-CooH-6-7-25-Naso-Wheres-the-Man-podcast-xxx.mp3 The combined two-part reading and Sabbath midrash:

This week, the 365 Amplified crew covers a range of timely and thought-provoking topics:

The Book of Bemidbar, or Numbers, which begins with the reading this week (Numbers 1:1-4:20) is apropos both in English, and in the Hebrew names. It certainly has LOTS of Numbers, and for very good reasons, and it takes place 'B'midbar,' or "In the Wilderness." Mark Call of Shabbat Shalom Mesa fellowship and the Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2025/05/SSM-5-30-25-Bemidbar-teaching-podcast-xx.mp3 The Sabbath Day midrash is about more than just the significance of the 'Numbers' that make up so much of the story. If "faith" was all that matters, why would He spend so much ink on numbers? And why is there so much information in here that doesn't really merit much attention from so much of 'christianity' anyway? What can we really learn from things that most would evidently prefer to ignore? Bemidbar: "Pay Attention to Scripture Ignored" https://hebrewnationonline.com/wp-content/uploads/2025/05/WT-CooH-5-31-25-Bemidbar-Pay-Attention-to-Things-IGNORED-Numbers-matter-podcast-xx.mp3 The combined two-part reading and Sabbath midrash:

The Book of Vayikra or Leviticus concludes with the two part torah parsha, "Behar," and "Bechukotai," (Leviticus chapters 25 through the end of the Book.) Covered first are the concepts of 'sabbath for the land,' and the "Jubilee" year, which Mark Call of Shabbat Shalom Mesa explains might be thought of as a big Reset button that has the effect of precluding a societal meltdown and depression otherwise. Mark Call of Shabbat Shalom Mesa fellowship and the Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2025/05/SSM-5-23-25-Behar-Bechukotai-teaching-podcast-xxx.mp3 The Sabbath Day midrash begins with a bit more background on that Scriptural reset, and what happens when it does NOT. And even though much of the parsha is directed at what happens "in the [promised] land" - and we remain in exile, as also promised - there are indications that we are again on the precipice of the multiplied curses in the latter part of the parsha, that again seem so clearly apropos. Behar-Bechukotai: "The Big Reset Lever - and What Follows" https://hebrewnationonline.com/wp-content/uploads/2025/05/SSM-5-23-25-Behar-Bechukotai-THE-Big-Reset-Lever-and-what-follows-podcast-xxx.mp3 The combined two-part reading and Sabbath midrash:

What if the most powerful tool for driving agile transformation isn't a framework or a ceremony—but a dashboard? Today's guest believes data may be the most underused lever for agility in large organizations. Gabrielle Wieczorek is a Scrum Master and Certified Agile Coach and a speaker at the upcoming Online Scrum Masters Summit, where she brings over 14 years of experience blending agile frameworks with data science, analytics, and stakeholder trust-building. About Gabrielle WieczorekGabrielle Wieczorek is an adaptive transformation leader with over 14 years of experience helping teams and organizations unlock the true potential of business and personal agility, especially in times of uncertainty. An enthusiastic Scrum Master, Certified Agile Coach (A-CSM, SSM), Product Owner (CSPO), and technical Senior Systems/Data Analyst, Gabrielle excels in leading teams through change and complexity, focusing on continuous improvement and delivering tangible results. Known for delivering engaging talks that make innovative agile concepts obtainable, Gabrielle has a knack for turning abstract ideas into real-world impact. Whether facilitating dynamic workshops or sharing insights in a lightning talk, Gabrielle empowers others to elevate their Agile practices and drive meaningful change in today's fast-paced, ever-evolving environments where efficiency and innovation are essential to success. RESOURCES Speaker, Online Scrum Masters Summit: https://onlinescrummastersummit.com/ https://onlinescrummastersummit.com/ This show is brought to you by the Online Scrum Masters Summit, taking place virtually on June 17-19, with more information at: www.onlinescrummasterssummit.com Catch the future of e-commerce at eTail Boston, August 11-14, 2025. Register now: https://bit.ly/etailboston and use code PARTNER20 for 20% off for retailers and brandsOnline Scrum Master Summit is happening June 17-19. This 3-day virtual event is open for registration. Visit www.osms25.com and get a 25% discount off Premium All-Access Passes with the code osms25agilebrandDon't Miss MAICON 2025, October 14-16 in Cleveland - the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

Terima kasih MYDATASSM – Sumber Maklumat Korporat Malaysia yang Dipercayai kerana sudi menaja episod ini! Dengan akses pantas dan mesra pengguna kepada data rasmi Suruhanjaya Syarikat Malaysia(SSM), MYDATASSM membantu anda membuat keputusan yang lebih tepat dan yakin - sama ada untuk urusan bisnes, membuka akaun bank perniagaan, semakan latar belakang, atau keperluan rasmi.Mantra kami, "Segalanya Mudah dengan MYDATA", mencerminkan komitmen kami untuk memudahkan proses anda, dari semakan maklumat syarikat hingga ke penyata kewangan dalam bentuk digital yang diiktiraf.Usahawan, penjawat awam, pelabur, atau orang awam — semuanya boleh bermula di sini.Cari, semak, dan yakin – hanya di MYDATASSM.Website: https://www.mydata-ssm.com.my/Instagram: https://www.instagram.com/mydatassm/Facebook: https://www.facebook.com/MyDataSSMX: https://x.com/MYDATASSMTiktok: https://www.tiktok.com/@mydatassmLinkedin: https://www.linkedin.com/company/bigdataworks/Get your SSM documents in a jiffy at MYDATA Express: 019-2797563Audio Siar Keluar Sekejap Episod 155 antaranya membincangkan langkah beberapa negeri yang mengharamkan penjualan vape, mencetuskan perdebatan mengenai keberkesanan dasar kesihatan awam serta perbezaan pendekatan antara kerajaan negeri dan persekutuan.Episod ini juga mengulas kenyataan bersama antara Petronas dan Petros, yang dilihat sebagai satu perkembangan penting dalam hubungan ekonomi antara kerajaan persekutuan dan Sarawak, khususnya dalam pengurusan sumber asli negeri.Turut dibincangkan adalah cadangan untuk menaikkan umur persaraan wajib kepada 65 tahun, dengan sorotan terhadap pro dan kontra dasar ini dari sudut kemampanan fiskal, peluang pekerjaan anak muda, dan kesejahteraan warga emas.Episod ini turut menyentuh Sidang Kemuncak ASEAN yang sedang berlangsung, termasuk peranan Malaysia dalam menghadapi cabaran serantau serta pertembungan kuasa-kuasa besar yang semakin ketara di Asia Tenggara.Ingin jenama anda dikenali oleh ribuan pendengar?Taja episod Keluar Sekejap untuk tahun 2025!Hubungi kami di +6011-1919 1783 atau emel ke commercial@ksmedia.my untuk maklumat lanjut dan pakej penajaan eksklusif.

This show is brought to you by the Online Scrum Masters Summit, taking place virtually on June 17-19, with more information at: http://www.onlinescrummasterssummit.com What if the most powerful tool for driving agile transformation isn't a framework or a ceremony—but a dashboard? Today's guest believes data may be the most underused lever for agility in large organizations. Gabrielle Wieczorek is a Scrum Master and Certified Agile Coach and a speaker at the upcoming Online Scrum Masters Summit, where she brings over 14 years of experience blending agile frameworks with data science, analytics, and stakeholder trust-building. About Gabrielle WieczorekGabrielle Wieczorek is an adaptive transformation leader with over 14 years of experience helping teams and organizations unlock the true potential of business and personal agility, especially in times of uncertainty. An enthusiastic Scrum Master, Certified Agile Coach (A-CSM, SSM), Product Owner (CSPO), and technical Senior Systems/Data Analyst, Gabrielle excels in leading teams through change and complexity, focusing on continuous improvement and delivering tangible results. Known for delivering engaging talks that make innovative agile concepts obtainable, Gabrielle has a knack for turning abstract ideas into real-world impact. Whether facilitating dynamic workshops or sharing insights in a lightning talk, Gabrielle empowers others to elevate their Agile practices and drive meaningful change in today's fast-paced, ever-evolving environments where efficiency and innovation are essential to success. RESOURCES This show is brought to you by the Online Scrum Masters Summit, taking place virtually on June 17-19, with more information at: www.onlinescrummasterssummit.com Catch the future of e-commerce at eTail Boston, August 11-14, 2025. Register now: https://bit.ly/etailboston and use code PARTNER20 for 20% off for retailers and brands Online Scrum Master Summit is happening June 17-19. This 3-day virtual event is open for registration. Visit www.osms25.com and get a 25% discount off Premium All-Access Passes with the code osms25agilebrand Don't Miss MAICON 2025, October 14-16 in Cleveland - the event bringing together the brights minds and leading voices in AI. Use Code AGILE150 for $150 off registration. Go here to register: https://bit.ly/agile150 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstrom Don't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.show Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

The Erev Shabbat (Friday evening) of two-part Double-parsha "Kedoshim," then "Emor," Leviticus chapters 19 through 24, is what Mark Call of Shabbat Shalom Mesa fellowship suggests is an interesting combination, given the number and relationships of the multitude of statutes, judgments, and commandments in this section. Some of it repeats the prohibition of sexual sins and even abominations outlined last week, but this time including penalties, while others literally "cover the map" - from things seem related, to many that don't -- almost like a scatter-gun. And it certainly makes for some interesting questions! The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2025/05/SSM-5-16-25-Kedoshim-Emor-teaching-podcast-xxx.mp3 The combination of these two paraschot includes what amounts to a 'tour de force' of proof texts why so much of the Whore Church has literally turned its back on Scripture. From sexuality, to economics, to the common law and even common decency, the fact that so much of what He says to do "forever," and even "throughout your generationss," and "in all your dwelling places," is not only now ignored, but considered "not PC," is more than telling. It's an indictment. Kedoship-Emor: "He Should Not Have To Say, 'No Trans Priests'" https://hebrewnationonline.com/wp-content/uploads/2025/05/WT-CooH-5-17-25-Kedoshim-Emor-No-Transgender-Priests-podcast-xxx.mp3 The combined two-part reading and Sabbath midrash:

Listen in as Jonathan A. Bernstein, MD, and Ryan Haumschild, PharmD, MS, MBA, CPEL, discuss how to manage the multidisciplinary care of patients with systemic mastocytosis (SM) from both the allergy/immunology and pharmacy perspective, including:Strategies to better identify patients presenting with features of SM to facilitate timely diagnosisCurrent guideline-recommended treatment approachesEmerging data on new targeted agents for SMPharmacist-led strategies to help patients achieve better outcomes (e.g., specialist referral, polypharmacy counseling, and anaphylaxis education)PresentersJonathan A. Bernstein, MDProfessor of MedicineDivision of Rheumatology, Allergy and ImmunologyDepartment of Internal MedicineUniversity of Cincinnati College of MedicinePartner Advanced Allergy Services, LLCPartner Bernstein Clinical Research Center, LLCCincinnati, OhioRyan Haumschild, PharmD, MS, MBA, CPELVice President of Pharmacy, AmbulatoryEmory HealthcareWinship Cancer InstituteAtlanta, GeorgiaFull link to program page:https://bit.ly/3HcA8z2

The annual Torah cycle reading for this week, Achre Mot, Leviticus chapters 16 through 18, takes place - literally as it says - "after the death" of Aaron's two sons, Nadab and Abihu. And it begins with a warning about what Aaron must do, so that he "die not," as well. The Erev Shabbat (Friday evening) begins there, and with a description of the 'two goats' associated with the Day of Atonement, or Yom Kippur. What then follows is another of the most "politially-INcorrect" sections in Scripture. And the fact that it IS tells us just how far into perversion the world has gone. And there is a warning here, too. The fact that SO much of what is today accepted as PC means that His Truth is now guaranteed to offend many. https://hebrewnationonline.com/wp-content/uploads/2025/05/SSM-5-9-25-Achre-Mot-teaching-podcast-xxx.mp3 it? As Yahushua warned in prophecies like Matthew chapter 24, we are currently seeing what is almost certainly the beginning of the period of the Greatest Deception in human history. So this Sabbath Day midrash begins with a warning, from Paul's Second Letter to the Thessalonians: those who do not have a "love of the Truth" will probably not survive what is coming. "Achre Mot: It Only STARTS with Love of the Truth" https://hebrewnationonline.com/wp-content/uploads/2025/05/WT-CooH-5-10-25-Achre-Mot-Love-of-Truth-Rightly-Divide-the-Word-podcast-xxx.mp3 The combined two-part reading and Sabbath midrash: https://hebrewnationonline.com/wp-content/uploads/2025/05/WT-CooH-5-10-25-Achre-Mot-Love-of-Truth-Rightly-Divide-the-Word-podcast-xxx.mp3

If you were to ask most 'sun-day christians' what one of the most boring, and irrelevant, sections of the whole Book is - even if they never hear it read anyway - many might point to the part about what they call "leprosy." Which is a good reason to at least SUSPECT that there's more to it. But Mark Call of Shabbat Shalom Mesa fellowship suggests this week that there is a WHOLE LOT more to it: Not only is the section NOT at all about "leprosy," or what we know as Hansen's Disease, there's a good case to be made, as he does, for the "why!" The Erev Shabbat (Friday evening) of the two-part Double-parsha "Tazria," then "Metzorah," Leviticus chapters 12 through 15.reading again begins with what happens on eighth day -- but this time it as after a woman "bears" a male child -- and one more thing that just isn't talked about much either: https://hebrewnationonline.com/wp-content/uploads/2025/05/SSM-5-2-25-Tazria-Metzora-teaching-podcast-xx.mp3 Once again, and as seems to be so often the case, the Torah portion story this week has a relevance to current events that demonstrates the timelessness of the message, EVEN if it has to do with a malady that hasn't been seen for well over a thousand years. But if the "Evil Tongue," ('lashon hora' in the Hebrew) has something to do with the plague, Mark has suggested in the past that there may be a reason. A fairly-standard warning about "gossip" [at least a subset of 'lashon hora'] is that it kills three people: the one who speaks it, the one who listens, and the one about whom it is spoken." And most discussion of the actual plague, called "tzaraat" in Hebrew, and there is no actual translation, tends to not only spiritualize, but personalize, the warning: 'Don't do it.' But could the reason we don't see that Divine Discipline manifested with people being marked as "unclean, unclean," be an aspect of something much bigger? And when did what has been referred to as "Supernatural Spiritual Discipline" actually come to an end? Or did it? Tazria-Matzorah: "The Truly GLOBAL Evil Tongue - and What It Means Today" https://hebrewnationonline.com/wp-content/uploads/2025/05/WT-CooH-5-3-25-Tazria-Metzora-CORPORATE-Empirical-PPP-Lashon-Hora-podcast-xxx.mp3 The combined two-part reading and Sabbath midrash:

Join Mark Call of Shabbat Shalom Mesa fellowship for a two-part look at parsha "Shmini," Leviticus chapters 9 through 11. The Erev Shabbat (Friday evening) reading begins with the story of the "eighth [shmini] day" and the events leading to the deaths of Aaron's two eldest sons. And it completes with the instruction of what is "food," and what is not. The confluence certainly suggests there is a connection, regardless of what we may have been told by many who, "by your traditions, make the commandments of YHVH of no effect." The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2025/04/SSM-4-25-25-Shmini-teaching-podcast-xxx.mp3 As seems to be so often the case, the Torah portion story this week has a relevance to current events that demonstrates the timelessness of the message, as the lawless claim that "no one is above the law," has become a sick joke. Mark notes that there has been much discussion over the centuries of why "Aaron kept his peace," or remained silent, after the death of his two oldest sons, Nadab and Abihu. One of the explanations might be that he realized, after the 'golden calf,' that he, himself, had arguably deserved, but been spared, a similar fate. So, why those two? What did they really do? Even though Scripture explicitly tells us, questions remain. Because, "to whom much is given, much is expected." Shmini: "No One is Above the Law. And they Knew, or Should Have Known." https://hebrewnationonline.com/wp-content/uploads/2025/04/WT-CooH-4-26-25-Shmini-NO-One-is-Above-the-Law-Knew-or-Should-Have-podcast-xxx.mp3 The combined two-part reading and Sabbath midrash:

Join Mark Call of Shabbat Shalom Mesa fellowship for a special "Holy-and-UN" Day rip-roaring discussion of things that don't fall into the regular annual Torah reading cycle, but are absolutely relevant 'for such a time as this.' For the Erev Shabbat (Friday evening) reading, Mark was led to examine Ezekiel's vision in chapters 8 and 9, in a story he refers to as the "angel with the inkhorn." And it is undeniably relevant to much of what is happening now, and this weekend in particular. The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2025/04/SSM-4-18-25-Dealers-Choice-special-teaching-for-Ishatar-sun-god-day-Ezekiel-8-9-podcast-xxx.mp3 During the 'change-of-pace' Sabbath Day message, Mark again takes up the theme of the current 'cusp,' or turning point, but with the understanding that we have been told that "things hidden will be revealed." (Matthew 10:26 et al) And it's not just pagan practices that have supposedly been 'christianized,' in spite of the fact that YHVH says so bluntly that He "hates" them. It's virtually every aspect of our world that you can name, from economics, to politics, to science...and even the no-longer-hidden open treason among those "Black-robed priests of Satan." Buckle up. This is one you won't want to miss! 419, False Flags, Fake Gods - Things Hidden Until Such a Time as This https://hebrewnationonline.com/wp-content/uploads/2025/04/WT-CooH-4-19-25-419-Things-Hidden-Being-Revealed-On-the-Cusp-podcast-xxxx.mp3 The combined two-part reading and Sabbath midrash:

The final Torah portion reading from the Book of Exodus is parsha "Pekudei" (the 'Accounts', Exodus 38:21 through the end of the Book) and it begins with exactly that: a recounting of the gold, silver, and brass that were used to complete the mishkan, or tabernacle in the wilderness. Again, too, there is much detail, almost to the point of redundancy, but for what appears to be an important reason. Almost word-for-word, what we had been told they WERE to do, is now recounted that they did. And, over and over again, it was "as Yahuah commanded Moses." Surely there is a lesson there. The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2025/03/SSM-3-28-25-Pekudei-teaching-podcast-x.mp3 This parsha seems to give an answer to the question, "Why?" Why build that 'mishkan' together? Why is that phrase "as Yahuah commanded Moshe," repeated eighteen TIMES in this parsha alone? Why does this still matter? Especially now? "Pekudei: As YHVH commanded Moshe - we had still better know and do" https://hebrewnationonline.com/wp-content/uploads/2025/03/WT-CooH-3-29-25-Pekudei-As-YHVH-Commanded-Moshe-so-WE-had-better-DO-podcast-xxx.mp3 The combined podcast is here:

Join Mark Call of Shabbat Shalom Mesa fellowship for a two-part look at parsha "Tzav" (Leviticus chapters 6 through 8). The first unique word in the portion is 'tzav', or COMMAND, Aaron and his sons, concerning more specifics associated with various types of offerings. And, it's important to note that the word translated as "this is the LAW" of these activities is again the root word 'torah,' and clearly makes more sense if we understand that this is INSTRUCTION about them. For many obvious reasons, we can't DO them, but we can study the instruction to try to understand what we are being taught. The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2025/04/SSM-4-11-25-Tzav-teaching-podcast-xx.mp3 We no longer have a temple, or mishkan. Nor cohenim to make the offerings. Except for admonitions like "don't eat blood," none of these things can really be done. Meanwhile, we live in a world where even the commandments and judgments which still obviously DO apply are scoffed at. Or worse. Which is why some "compare and contrast" with where we find ourselves today, relative to history, and prophecy, should be informative. Mark suggests we are at a 'cusp,' or turning point, but almost like the "calm before the storm." Consider "dishonest weights and measures," for example. Whatever the new President's intention, he inherited a fiat dollar that Scripture calls "abomination," and which WILL ultimately collapse. The question is not 'IF,' but when. And, what will survive? But Scripture and prophecy give us an answer there, too. Tzav: Do We Still Trust in Lying Words? https://hebrewnationonline.com/wp-content/uploads/2025/04/CooH-4-12-25-Tzav-On-the-Cusp-podcast-xxx.mp3 The combined two-part reading and Sabbath midrash:

Subscriber-only episodeThe tables have turned. This time, SSM interviews HSD!Learn a lot more about HSD after he answers all your fan submitted questions uncovering a little of how he is in his vanilla life, what his thoughts are on the BF/GF dynamic SSM has with SoCal, his advice for couples interested in hotwifing and much more...but most importantly, HSD spills the beans about his go-to order from In-N-Out!Don't miss this one!Visit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

This week we begin the reading and study of the Book of Vayikra, or Leviticus, with chapters 1 through 5. And, sadly, this is one of those Books where some folks just hear the name ('Leviticus') and their eyes begin to glaze over; "it's SO boring," and "what difference does it make anyway?" Which is the best reason you'll hear to take an honest look at what it really says, why it matters NOW, more than ever, and why we have been lied to so thoroughly about all of it. Because you can't understand the real Messiah, or recognize the fakes, without understanding what we have almost certainly NOT been taught! Starting with the overview, and reading, to understand a bit of that distinction: https://hebrewnationonline.com/wp-content/uploads/2025/04/SSM-4-4-25-Vayikra-teaching-podcast-xxx.mp3 The Sabbath day in-depth 'midrash' picks up with that vital distinction. And, WARNING: This will upset some folks, because John had it right. (I John chapter 2) He who says, “I know Him,” and does not keep His commandments, is a liar, and the truth is not in him. And that describes accurately what Mark Call refers to as BOTH the 'Whore Church," and the "Whore Synagogue." And this is where it will be made very clear why that is not only accurate, but vital to understand. Yes, many if not most of us who have attended the vast majority of 'denominational churches' have probably heard the term "Old" Testament, and one of the Biggest Lies in all of history: that somehow "Jesus did away with the Law," or "nailed it to the cross," so nothing the Bible says about "sacrifices" matters any more. Could it be that there is something vitally important that is missing? This week those "battle lines" became ever more clear. Vayikra: AI-dolatry -- When Does Mere Ignorance Become Outright Rebellion to YHVH? https://hebrewnationonline.com/wp-content/uploads/2025/04/WT-CooH-4-5-25-Vayikra-AIdolatry-Teaching-INTENTIONAL-sin-to-the-Deliberately-Ignorant-xxx.mp3 The combined two-part reading and Sabbath midrash:

The Torah reading called "Pekudei" (for the "accounts" that summarized the making of the 'mishkan,' or Tabernacle in the Wilderness, from Exodus 38:10 through the end of the Book) is the final parsha the the opening saga of the Exodus. And while the story has only really begun at that point, it's an inspired summary of what mattered then, and still does:  the phrase "as YHVH commanded Moshe [Moses]" is repeated eighteen times in this parsha alone, and the level of repeated detail on the work the 'mixed multitude' did together is, in large measure, also repeated, but with a change of tense:  that which they were TOLD to do, they, and Moses, DID -- and, again, "as YHVH commanded Moshe." There is clearly a message there. While most of us who have attended the vast majority of 'denominational churches' have probably heard the term "Old" Testament, and even that "the Law" was somehow away with later, as if it no longer applies, and what matters instead is the 'spirit' that is in our hearts, Mark Call of Shabbat Shalom Mesa suggests we had better understand the MANY other admonitions in Scripture, including warnings from Shaul, or Paul, that have been twisted.  He starts with a look at the First Letter Paul wrote to the Corinthians, and chapter 3.  But it is undeniable, to those with "eyes to see," that the ReNewed Covenant, in places like Jeremiah 31:31 is not quite what most of us have been taught, either. As we see the battle lines being drawn in a world which has largely rejected the True Messiah in favor of "another jesus whom we have NOT preached," Mark suggests it has never been more important not only that we know WHICH Spirit is "holy" and how to know, but that we understand why what "Yahuah commanded Moshe" is still the Foundation -- just as Yahushua HaMashiach, the Messiah, said, and taught.  He never changed so much as a "yod or tiddle." And He summarized it all simply, too:   "If you love Me, keep My commandments." Which?  All of 'em.  The ones He Wrote, and Taught, and has never changed. If we are now to be His "temple," and His Holy Spirit is to dwell within our hearts, we need to understand what that really means. The Erev Shabbat Reading of the entire portion: https://hebrewnationonline.com/wp-content/uploads/2025/03/SSM-3-28-25-Pekudei-teaching-podcast-x-1.mp3 Pekudei: As YHVH Commanded Moshe - so we still had better DO https://hebrewnationonline.com/wp-content/uploads/2025/03/WT-CooH-3-29-25-Pekudei-As-YHVH-Commanded-Moshe-so-WE-had-better-DO-podcast-xxx-1.mp3 The combined two-part reading and Sabbath midrash: https://hebrewnationonline.com/wp-content/uploads/2025/03/WT-CooH-3-29-25-Pekudei-As-YHVH-Commanded-Moshe-so-WE-had-better-DO-podcast-xxx-1.mp3

Subscriber-only episodePart 2 of 2 of your questions for Sexxxy Soccer Mom!What makes someone good in bed?  When's our pending divorce?  And when is SSM going to shack up with Liam Hemsworth?Tune in, it's a fun one!Visit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

Subscriber-only episodeThat's right, it's Sexxxy Soccer Mom's time to take a turn in the hot seat!Sit back, grab a snack, and listen to this fun episode where HSD asked questions that you, our wonderful fans, asked specifically for SSM to answer!Visit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

This may be one of the most important - and certainly controversial - teachings that Mark Call, of Shabbat Shalom Mesa Fellowship has done. Because it hits at the very heart of what "Come out of her, My people," is about. Parsha "Ki Tisa" (Exodus chapters 30 through 34) includes on of the most infamous tragedies in the Bible - the story of the 'Golden Calf,' and Moses' subsequent throwing down and destruction of the first set of tablets, engraved with the very 'finger of YHVH.' And that, too, is symbolic of what has been done by the mob that "assembled" or "gathered" against Aaron ever since! The Erev Shabbat reading of the portion includes some of the vital context for the story that often tends to be overlooked, given the drama that follows: https://hebrewnationonline.com/wp-content/uploads/2025/03/SSM-3-14-25-Ki-Tisa-teaching-podcast-xxx.mp3 What is less well-understood is that the entire context of that story reflects on what another "assembly" (or, even 'ecclesia' for those that have heard the Greek term) has done almost universally, over and over again, throughout history. And still continues. The Sabbath Day midrash addresses the 'twisting' that Kefa/Peter talked about (II Peter 3:15-16) and how, in particular, Paul's second letter to the Corinthians has been almost completely "turned on its head," as is seem by a look at this story, and the context of chapter 3 of that Book. [Hebrew Nation Radio is having some server issues - this will be uploaded later...] If you find this valuable, or even shocking - please share it. As the Bible makes clear, it really is a matter of life and death. Both segments are combined here:

Parsha "Tetzaveh" (Exodus 27:10 - 30:10) continues the description of elements associated with the still-to-be-built 'tabernacle in the wilderness,' this time beginning with the priestly garments for Aaron and his sons. The Erev Shabbat Reading begins with "command" them to make oil for the menorah, and then continues through the sanctification of the 'cohenim': https://hebrewnationonline.com/wp-content/uploads/2025/03/SSM-3-7-25-Tetzaveh-teaching-podcast-x.mp3 The Sabbath Day midrash concerns a conjunction of events, both historic and current, and associated readings. And as seems to so often be the case, there's more than just coincidence evidently at work now. One of the obvious, and stated, purposes of the garments created "for splendor and for beauty," to be worn by the cohenim (priests) was that they be "set apart" to serve YHVH. And the golden inscription on Aaron's forehead said, "Holy to YHVH." The fact that such a priesthood no longer exists only makes the contrast more clear. But several events this week really brought that home. By almost any Scriptural measure, what we now have instead looks like an "anti-priesthood," set apart not to YHVH, but His "Adversary." And an honest reading of Scripture is "uncomfortably clear" on those implications. Note: The midrash mentions a related look at the story of Esther, and the 'Purim' holiday, which was an element of Mark's observations in the "Come out of her, My people" Show this week: https://hebrewnationonline.com/come-out-of-her-my-people-show-mark-call-weekly-274/ Tetzaveh: What is Amalek?

Parsha "Terumah" (Exodus 25:1 - 27:19) is a major change of pace from the story of the plagues, and the Exodus from bondage in Egypt. While Moses is evidently still up on the mountain, he is told by YHVH to take an 'offering' (terumah) from those with willing hearts. And then follows a description of specifically what, and what it is for. The Erev Shabbat Reading: https://hebrewnationonline.com/wp-content/uploads/2025/03/SSM-2-28-25-Terumah-teaching-podcast-x.mp3 The level of detail in the parsha this week, and even subsequently, is almost an enigma: It is almost overwhelming, and yet were it not for the fact that Moses is told that he is being shown a 'pattern,' or "blueprint," it is pretty evident that what is being described could probably not be built. And it must be done by the effort of the 'skillful workman,' besides. Later, we're even told that those tasked with that work must even be guided by the very Ruach Elohim, or Spirit of YHVH. Many of us, because this is the "Olde" Testament, after all, have probably heard that anything associated with the 'tabernacle' (or later temple) is superfluous now, and even "done away with." Or it's just 'spiritualized' - perhaps even with a bit too much hand-waving. So, even the level of detail included is just not enough, in the sense of being able to completely understand the design... There's something very telling about that. Terumah: Why does the detail seem overwhelming? https://hebrewnationonline.com/wp-content/uploads/2025/03/WT-CooH-3-1-25-Terumah-Detail-can-overwhelm-if-the-BLUEPRINT-is-Wrong-podcast-xxx.mp3 The combined two-part reading and Sabbath day midrash is here:

Parsha "Mishpatim" (Exodus chapters 21 through 24) is literally "judgments," or "ordinances," and begins with a number of them. But what is most fascinating about them is that so many are now considered NOT 'politically-correct,' and that fact alone merits taking a special look at why. The Erev Shabbat Reading: https://hebrewnationonline.com/wp-content/uploads/2025/02/SSM-2-21-25-Mishpatim-teaching-podcast-xxx.mp3 Mark has long remarked about the fact that this parsha, Mishpatim, is SO very NOT PC. But this year, we need to take note of an important change. People seem to have just about "had it" with men pretending to dominate 'womens' sports', and kids being taught utter perversion - and worse - in the public cesspools. And just about everything else that amounts to "calling evil good," and vice-versa. And the level of utter corruption and criminality in an illegitimate government that was NEVER supposed to be a 'democracy' in the first place has inclined more people to ask just how we could have been so deceived for so long. Perhaps the answer is in one of the key verses - also too often ignored - in this parsha as well: "Do not follow after a multitude to do evil." Could that include even a 'majority vote'? Mishpatim: DEMOLISH PC Idolatry - finally NOTE: The HNR website had difficulty loading the separate MP3 file for the Sabbath day teaching alone - so I had to go with a single combined file; the Friday reading is thus on there twice, as some have noticed.

Subscriber-only episodeIt has been a busy February so listen in as SSM and HSD recap some pretty incredible dates this month!There was a birthday celebration, some Valentine's Day fun and a super, Super Bowl get together for the ages!SSM has a big announcement that you won't want to miss!Visit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

It has been a busy February so listen in as SSM and HSD recap some pretty incredible dates this month!  There was a birthday celebration, some Valentine's Day fun and a super, Super Bowl get together for the ages!  SSM has a big announcement that you won't want to miss!Subscribe at www.patreon.com/theadventuresofahotwife to listen to this complete episode and much more, including complimentary access to our Discord server.Support the showVisit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

Parsha "Yitro" (Exodus chapters 18 through 21) is named for the man who is Moses' father-in-law, because he makes an appearance in the very first part of the story. But the portion is most noted because it includes the first giving of the 'Ten Debarim' (actually 'words,' or even Ten Sayings) - most usually rendered in English as the Ten Commandments. The Erev Shabbat Reading: https://hebrewnationonline.com/wp-content/uploads/2025/02/SSM-2-14-25-Yitro-teaching-podcast-x.mp3 The description surrounding the fact that the mixed multitude of Israel, according to the literal Hebrew, actually "SAW" the thunderings, and the other aspects of the interaction were so overwhelming that they then told Moses, 'YOU speak to us,' from here on out, because they were afraid that if they heard directly from YHVH again, it would kill them, is a graphic indication that THIS interaction with the Creator of the Universe was different than anything that had ever happened before. And it's something that Mark Call has "waxed a bit nerdy" about before, suggesting that it was some type of "high bandwidth" download that probably seemed overwhelming to them. And, superficially at least, but maybe even to a deeper extent given the level of incredible Evil now being exposed, we may be seeing a similar level of "information overload" today. But the similarities don't stop there. Yitro: They heard - er, saw - but didn't LISTEN! https://hebrewnationonline.com/wp-content/uploads/2025/02/WT-CooH-2-15-25-Yitro-They-heard-no-SAW-but-did-NOT-Listen-podcast-xxx.mp3

Parsha "B'shalach" (Exodus 13:17 - 17:16) begins with what might be the most famous miracle in the Bible, the "parting of the Red Sea" [more likely the 'Sea of Reeds'] and the related destruction of Pharaoh, and all his army and chariots. The very first verse of the parsha, as Mark Call notes in the reading, should perhaps "leap off the page" today as a warning: YHVH took the 'mixed multitude' via the Long Way Home to the Promised Land, rather than the shorter coastal route, "lest the people regret," when they see war, and decide to return right back into bondage. Could that ring true today? The Erev Shabbat Reading: https://hebrewnationonline.com/wp-content/uploads/2025/02/SSM-2-7-25-Bshalach-teaching-podcast-xx.mp3 The question has been asked. But there is something fundamental about human nature that is outlined here. Rather than being grateful for having been freed "by a Mighty Hand," from bondage, and happy to be en route to a Promised Land, why instead do people whine, and want to go back into slavery? In that context it is interesting that there is so much emphasis in this story on "testing" by YHVH. They see thirst in the wilderness. And have cause for concern when He gives them 'bread from heaven' - before it gets a name. The Sabbath is introduced. (Or - is it RE-introduced?) But Yah has good reason to ask, "How long will you refuse to keep My commandments and My Instruction?" B'shalach: Grateful? Or Whining? The Testing Is Yet to Come https://hebrewnationonline.com/wp-content/uploads/2025/02/WT-CooH-2-8-25-Bshalach-The-Testing-to-Come-Grateful-or-Whining-podcast-xx.mp3 The combined two-part teaching will be up later; HNR has server problems that prevented it from uploading.

Subscriber-only episodePlease welcome the gorgeous Hotwife Sadie to the show!On this episode, our fabulous part-time cohost RealHotwife and SSM to this stunning hotwife and rising star about the balance between her LS and content life.  Cum listen as she discusses how her first experience was getting her tit sucked by her (and her husband's) roommate while pregnant (in fact, we talk pregnancy and hormones and how they affect tit size) and why they got into the lifestyle (hint...it's not why you think), her relationship with her husband and boyfriend and how they make it work for them, and her quick climb in the content world.It's a fun and very informative episode that dives into the different dynamics people experience when they open up their marriage and their sex life.Follow https://x.com/thesadierw for lots more of Sadie!Visit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

Parsha "Bo" (Exodus 10:1 - 13:16) describes the last three of the 'Ten Plagues of Egypt." And, in the process, lays out the understanding of the most important, the 'death of the firstborn,' and the first of His Appointed Times, Pesach; aka "the Passover." In the Erev Shabbat reading, Mark Call of Shabbat Shalom Mesa fellowship, outlines the reason why these might better be thought of as the final two of the third set of three plagues, followed by the one which in fact is in a category by itself: https://hebrewnationonline.com/wp-content/uploads/2025/02/SSM-1-31-25-Bo-teaching-podcast-xxx.mp3 The Sabbath Day midrash might be considered part two in a sequence, and begins with an examination of thise patters - multiple patterns in fact - that make up those "three sets of three" setup plagues, and, in particular, what they might show us about a future set of events that he again suggests will unfold at some time in the future. Certainly they were not only all judgments against various fake Egyptian 'gods,' but other patterns within the plagues, such as who and what they affected, and how, may give us a great picture of what the judgments against 'modern gods' might well look like. And what we should be prayerfully prepared for. also, Mark contends, a set of 'open brackets,' or one half of a set of bookends, which we will eventually see closed by the prophesied second, or "Greater Exodus." And there are certainly "candidates" for those in play today. So, sometimes a bit of speculation is useful. Bo: Patterns - the Next Set of Plagues" https://hebrewnationonline.com/wp-content/uploads/2025/02/WT-CooH-2-1-25-Bo-Patterns-The-NEXT-sets-of-Plagues-xxx.mp3 The combined two-part teaching is here:

Subscriber-only episodeJoin us for a bonus episode where we chat about SSM and SoCal's hook up this weekend, a fun and very friendly wager on the NFC Championship game and how HSD cheated his way to victory!Visit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

Subscriber-only episodeJoin RealHotWife, On the Rocks Girl and SSM as they discuss how they lost their virginities, getting banned from Tinder, an upcoming trip, and following silver balloons.  We also read some of our weirdest DMs and talk about why getting old is bad for being a slut.As expected, this one is a shitshow!Visit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

The second Torah portion reading from the Book of Exodus this week is in some respects THE beginning of the Exodus itself, in that it describes the first set(s) of the 'Ten Plagues of Egypt." 'Vaera' (Exodus 6:4 through chapter 9), beings, however, with an explanation of His Name, YHVH. "And I appeared," ('vaera') He says, to Abraham, and to Yitzak, and to Yakov, "as El Shaddai, but by My Name YHVH I did not," at not in the way that He is about to, "make Myself known to them. And that is the essence of what He is about to do! The Erev Shabbat reading, as usual, covers the story itself, but also starts to lay out the incredible significance of just what that means: https://hebrewnationonline.com/wp-content/uploads/2025/01/SSM-1-24-25-Vaera-teaching-podcast-xxx.mp3 The Sabbath Day midrash takes a deeper look at a number of key elements that are laid out in this parsha, from the emphasis on His Name YHVH, and that He would then SHOW what that means, so that all of us would know, to the patterns and projections associated with the plagues themselves. They were not only all judgments against various fake Egyptian 'gods,' but also, Mark contends, a set of 'open brackets,' or one half of a set of bookends, which we will eventually see closed by the prophesied second, or "Greater Exodus." And there are certainly "candidates" for those in play today. Vaera: What's it Gonna TAKE?" https://hebrewnationonline.com/wp-content/uploads/2025/01/WT-CooH-1-25-25-Vaera-Whats-It-Gonna-TAKE-podcast-xxx.mp3 The combined two-part teaching is here:

Join RealHotWife, On the Rocks Girl and SSM as they discuss how they lost their virginities, why you shouldn't drop your kids off at places, getting banned from Tinder, an upcoming trip, and following silver balloons.  We also read some of our weirdest DMs and talk about why getting old is bad for being a slut.As expected, this one is a shitshow!Listen to the entire episode right here: https://www.patreon.com/c/theadventuresofahotwifeSupport the showVisit https://linktr.ee/sexxxysoccermom to see a whole lot more of Sexxxy Soccer Mom!

The first Torah portion reading from the Book of Exodus this week is 'Shemot' (Exodus 1:1-6:2), which is of course the Hebrew name of the Book as well. And it begins the story of Moses (Moshe) and the Exodus from Egypt, and bondage, but actually begins even a bit earlier, and about two centuries after the story of Joseph in Genesis comes to an end. The Erev Shabbat reading not only introduces us to Moses, but actually covers about two-thirds of the span of his life in just a few chapters. Perhaps it's encouraging to consider that the most important part of his life's work didn't even begin until about his ninth decade: https://hebrewnationonline.com/wp-content/uploads/2025/01/SSM-1-17-25-Shemot-teaching-podcast-xxx.mp3 How did a people who were literally the "Sons of Israel," and direct descendants of the patriarchs, Abraham, Isaac, and Jacob, manage to descend from direct promises and blessings from the Creator Himself, to "cruel bondage" in just over two centuries? And for that matter, how do a people who understood "self-evident Truths" about that same Creator manage to descend to what may be even greater tyranny and bondage to an entirely different 'god' in almost that same times span? There is more here than you might think. Especially when you consider where we are on that timeline. Shemot: What HAPPENED to the 'Sons of Israel'? And how did they manage to go from such blessing to "cruel bondage?" https://hebrewnationonline.com/wp-content/uploads/2025/01/WT-CooH-1-18-25-Shemot-What-HAPPENED-podcast-xxxx.mp3 The combined two-part teaching is here:

The annual-cycle Torah reading week, parsha Vayechi (Genesis/Bereshiet chapter 47:28-End) not only concludes the story of the life and times of Yakov or Jacob, but of Yosef (Joseph) as well, and the Book of Genesis. The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2025/01/SSM-1-10-25-Vayechi-teaching-podcast-xx.mp3 Among other things, including Yakov's blessings for his sons, and thus the tribes of Israel, this parsha includes the 'adoption' of Yosef's two sons, Ephraim and Manasseh (or is it Manasseh and Ephraim???) into the "twelve" bribes of Israel. Where Yakov "crosses his hands," during that blessing. He asks a question, too. Which seems almost out of place. And yet, it's also almost as easy for us to just gloss over it, and ignore the potential implications. But is should resonate with us now: Vayechi: Whose are these? And Who's are WE? https://hebrewnationonline.com/wp-content/uploads/2025/01/WT-CooH-1-11-25-Vayechi-Whose-are-WE-podcast-xxx.mp3 The combined two-part teaching is here:

¡No guarde el abrigo! Continúa frente frío No. 23 en el país Gaza está cerca de un alto al fuego: Jake Sullivan Más información en nuestro podcast

The reading form the Torah this week, parsha Vayigash (Genesis/Bereshiet chapter 44:17-47:27) picks up at the last, dramatic, "cliff-hangar," in the third reading dealing with the life and times of Yosef (Joseph). And it begins with one of the most dramatic transformations in the Bible, in what Mark Call refers to as "Judah 'Mans Up.' And this is demonstrably the first time in history where one human being forgives another. The Erev Shabbat reading of the finale of the story: https://hebrewnationonline.com/wp-content/uploads/2025/01/SSM-1-3-25-Vayigash-teaching-podcast-xxx.mp3 There are again a number of major themes in the study of Joseph, and Judah in particular as well this week, and certainly of a different nature than what we saw previously. And it starts with a transformation. Judah, the brother who suggested that Joseph be sold into slavery, and then returned lied to his father about what happened, ends up facing almost EXACTLY the same situation, over two decades later, with Joseph's youngest brother. What he does THIS time marks him as worthy of being the father of THE line of kings. Joseph recognizes what he has become. Vayigash: Judah 'Mans Up' and Joseph Forgives - Two Sides of the Same Coin https://hebrewnationonline.com/wp-content/uploads/2025/01/WT-CooH-1-4-25-Vayigash-Man-Up-Forgiveness-2-Sides-of-the-Same-Coin-podcast-xxx.mp3 The combined two-part teaching is here:

Happy holidays! We'll be sharing snippets from Latent Space LIVE! through the break bringing you the best of 2024! We want to express our deepest appreciation to event sponsors AWS, Daylight Computer, Thoth.ai, StrongCompute, Notable Capital, and most of all all our LS supporters who helped fund the gorgeous venue and A/V production!For NeurIPS last year we did our standard conference podcast coverage interviewing selected papers (that we have now also done for ICLR and ICML), however we felt that we could be doing more to help AI Engineers 1) get more industry-relevant content, and 2) recap 2024 year in review from experts. As a result, we organized the first Latent Space LIVE!, our first in person miniconference, at NeurIPS 2024 in Vancouver.Of perennial interest, particularly at academic conferences, is scaled-up architecture research as people hunt for the next Attention Is All You Need. We have many names for them: “efficient models”, “retentive networks”, “subquadratic attention” or “linear attention” but some of them don't even have any lineage with attention - one of the best papers of this NeurIPS was Sepp Hochreiter's xLSTM, which has a particularly poetic significance as one of the creators of the LSTM returning to update and challenge the OG language model architecture:So, for lack of a better term, we decided to call this segment “the State of Post-Transformers” and fortunately everyone rolled with it.We are fortunate to have two powerful friends of the pod to give us an update here:* Together AI: with CEO Vipul Ved Prakash and CTO Ce Zhang joining us to talk about how they are building Together together as a quote unquote full stack AI startup, from the lowest level kernel and systems programming to the highest level mathematical abstractions driving new model architectures and inference algorithms, with notable industry contributions from RedPajama v2, Flash Attention 3, Mamba 2, Mixture of Agents, BASED, Sequoia, Evo, Dragonfly, Dan Fu's ThunderKittens and many more research projects this year* Recursal AI: with CEO Eugene Cheah who has helped lead the independent RWKV project while also running Featherless AI. This year, the team has shipped RWKV v5, codenamed Eagle, to 1.5 billion Windows 10 and Windows 11 machines worldwide, to support Microsoft's on-device, energy-usage-sensitive Windows Copilot usecases, and has launched the first updates on RWKV v6, codenamed Finch and GoldFinch. On the morning of Latent Space Live, they also announced QRWKV6, a Qwen 32B model modified with RWKV linear attention layers. We were looking to host a debate between our speakers, but given that both of them were working on post-transformers alternativesFull Talk on YoutubePlease like and subscribe!LinksAll the models and papers they picked:* Earlier Cited Work* Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention* Hungry hungry hippos: Towards language modeling with state space models* Hyena hierarchy: Towards larger convolutional language models* Mamba: Linear-Time Sequence Modeling with Selective State Spaces* S4: Efficiently Modeling Long Sequences with Structured State Spaces* Just Read Twice (Arora et al)* Recurrent large language models that compete with Transformers in language modeling perplexity are emerging at a rapid rate (e.g., Mamba, RWKV). Excitingly, these architectures use a constant amount of memory during inference. However, due to the limited memory, recurrent LMs cannot recall and use all the information in long contexts leading to brittle in-context learning (ICL) quality. A key challenge for efficient LMs is selecting what information to store versus discard. In this work, we observe the order in which information is shown to the LM impacts the selection difficulty. * To formalize this, we show that the hardness of information recall reduces to the hardness of a problem called set disjointness (SD), a quintessential problem in communication complexity that requires a streaming algorithm (e.g., recurrent model) to decide whether inputted sets are disjoint. We empirically and theoretically show that the recurrent memory required to solve SD changes with set order, i.e., whether the smaller set appears first in-context. * Our analysis suggests, to mitigate the reliance on data order, we can put information in the right order in-context or process prompts non-causally. Towards that end, we propose: (1) JRT-Prompt, where context gets repeated multiple times in the prompt, effectively showing the model all data orders. This gives 11.0±1.3 points of improvement, averaged across 16 recurrent LMs and the 6 ICL tasks, with 11.9× higher throughput than FlashAttention-2 for generation prefill (length 32k, batch size 16, NVidia H100). We then propose (2) JRT-RNN, which uses non-causal prefix-linear-attention to process prompts and provides 99% of Transformer quality at 360M params., 30B tokens and 96% at 1.3B params., 50B tokens on average across the tasks, with 19.2× higher throughput for prefill than FA2.* Jamba: A 52B Hybrid Transformer-Mamba Language Model* We present Jamba, a new base large language model based on a novel hybrid Transformer-Mamba mixture-of-experts (MoE) architecture. * Specifically, Jamba interleaves blocks of Transformer and Mamba layers, enjoying the benefits of both model families. MoE is added in some of these layers to increase model capacity while keeping active parameter usage manageable. * This flexible architecture allows resource- and objective-specific configurations. In the particular configuration we have implemented, we end up with a powerful model that fits in a single 80GB GPU.* Built at large scale, Jamba provides high throughput and small memory footprint compared to vanilla Transformers, and at the same time state-of-the-art performance on standard language model benchmarks and long-context evaluations. Remarkably, the model presents strong results for up to 256K tokens context length. * We study various architectural decisions, such as how to combine Transformer and Mamba layers, and how to mix experts, and show that some of them are crucial in large scale modeling. We also describe several interesting properties of these architectures which the training and evaluation of Jamba have revealed, and plan to release checkpoints from various ablation runs, to encourage further exploration of this novel architecture. We make the weights of our implementation of Jamba publicly available under a permissive license.* SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers* We introduce Sana, a text-to-image framework that can efficiently generate images up to 4096×4096 resolution. Sana can synthesize high-resolution, high-quality images with strong text-image alignment at a remarkably fast speed, deployable on laptop GPU. Core designs include: * (1) Deep compression autoencoder: unlike traditional AEs, which compress images only 8×, we trained an AE that can compress images 32×, effectively reducing the number of latent tokens. * (2) Linear DiT: we replace all vanilla attention in DiT with linear attention, which is more efficient at high resolutions without sacrificing quality. * (3) Decoder-only text encoder: we replaced T5 with modern decoder-only small LLM as the text encoder and designed complex human instruction with in-context learning to enhance the image-text alignment. * (4) Efficient training and sampling: we propose Flow-DPM-Solver to reduce sampling steps, with efficient caption labeling and selection to accelerate convergence. * As a result, Sana-0.6B is very competitive with modern giant diffusion model (e.g. Flux-12B), being 20 times smaller and 100+ times faster in measured throughput. Moreover, Sana-0.6B can be deployed on a 16GB laptop GPU, taking less than 1 second to generate a 1024×1024 resolution image. Sana enables content creation at low cost. * RWKV: Reinventing RNNs for the Transformer Era* Transformers have revolutionized almost all natural language processing (NLP) tasks but suffer from memory and computational complexity that scales quadratically with sequence length. In contrast, recurrent neural networks (RNNs) exhibit linear scaling in memory and computational requirements but struggle to match the same performance as Transformers due to limitations in parallelization and scalability. * We propose a novel model architecture, Receptance Weighted Key Value (RWKV), that combines the efficient parallelizable training of transformers with the efficient inference of RNNs.* Our approach leverages a linear attention mechanism and allows us to formulate the model as either a Transformer or an RNN, thus parallelizing computations during training and maintains constant computational and memory complexity during inference. * We scale our models as large as 14 billion parameters, by far the largest dense RNN ever trained, and find RWKV performs on par with similarly sized Transformers, suggesting future work can leverage this architecture to create more efficient models. This work presents a significant step towards reconciling trade-offs between computational efficiency and model performance in sequence processing tasks.* LoLCATs: On Low-Rank Linearizing of Large Language Models* Recent works show we can linearize large language models (LLMs) -- swapping the quadratic attentions of popular Transformer-based LLMs with subquadratic analogs, such as linear attention -- avoiding the expensive pretraining costs. However, linearizing LLMs often significantly degrades model quality, still requires training over billions of tokens, and remains limited to smaller 1.3B to 7B LLMs. * We thus propose Low-rank Linear Conversion via Attention Transfer (LoLCATs), a simple two-step method that improves LLM linearizing quality with orders of magnitudes less memory and compute. * We base these steps on two findings. * First, we can replace an LLM's softmax attentions with closely-approximating linear attentions, simply by training the linear attentions to match their softmax counterparts with an output MSE loss ("attention transfer").* Then, this enables adjusting for approximation errors and recovering LLM quality simply with low-rank adaptation (LoRA). * LoLCATs significantly improves linearizing quality, training efficiency, and scalability. We significantly reduce the linearizing quality gap and produce state-of-the-art subquadratic LLMs from Llama 3 8B and Mistral 7B v0.1, leading to 20+ points of improvement on 5-shot MMLU. * Furthermore, LoLCATs does so with only 0.2% of past methods' model parameters and 0.4% of their training tokens. * Finally, we apply LoLCATs to create the first linearized 70B and 405B LLMs (50x larger than prior work). * When compared with prior approaches under the same compute budgets, LoLCATs significantly improves linearizing quality, closing the gap between linearized and original Llama 3.1 70B and 405B LLMs by 77.8% and 78.1% on 5-shot MMLU.Timestamps* [00:02:27] Intros* [00:03:16] Why Scale Context Lengths? or work on Efficient Models* [00:06:07] The Story of SSMs* [00:09:33] Idea 1: Approximation -> Principled Modeling* [00:12:14] Idea 3: Selection* [00:15:07] Just Read Twice* [00:16:51] Idea 4: Test Time Compute* [00:17:32] Idea 2: Hardware & Kernel Support* [00:19:49] RWKV vs SSMs* [00:24:24] RWKV Arch* [00:26:15] QWRKWv6 launch* [00:30:00] What's next* [00:33:21] Hot Takes - does anyone really need long context?Transcript[00:00:00] AI Charlie: We're back at Latent Space Live, our first mini conference held at NeurIPS 2024 in Vancouver. This is Charlie, your AI co host. As a special treat this week, we're recapping the best of 2024 going domain by domain. We sent out a survey to the over 900 of you who told us what you wanted, and then invited the best speakers in the Latent Space Network to cover each field.[00:00:24] AI Charlie: 200 of you joined us in person throughout the day, with over 2200 watching live online. Thanks Our next keynote covers the State of Transformers alternative architectures, with a special joint presentation with Dan Fu of Together AI and Eugene Chia of Recursal AI and Featherless AI. We've featured both Together and Recursal on the pod before, with CEO Veepal Vedprakash introducing them.[00:00:49] AI Charlie: And CTO CE Zhang joining us to talk about how they are building together together as a quote unquote full stack AI startup from the lowest level kernel and systems [00:01:00] programming to the highest level mathematical abstractions driving new model architectures and inference algorithms with notable industry contributions from Red Pajama V2, Flash Attention 3, Mamba 2, Mixture of Agents.[00:01:15] AI Charlie: Based, Sequoia, Evo, Dragonfly, Danfoo's Thunder Kittens, and many more research projects this year. As for Recursal and Featherless, we were the first podcast to feature RWKV last year, and this year the team has shipped RWKV v5, codenamed Eagle, to 1. 5 billion Windows 10 and Windows 11 machines worldwide to support Microsoft's on device, end Energy Usage Sensitive Windows Copilot Use Cases and has launched the first updates on RWKV v6, codenamed Finch and Goldfinch.[00:01:53] AI Charlie: On the morning of Latent Space Live, they also announced QRdata UKv6, a QEN32B model [00:02:00] modified with RDWKV linear attention layers. Eugene has also written the most single most popular guest post on the Latent Space blog this year. Yes, we do take guest posts on what he has discovered about the H100 GPU inference NeoCloud market since the successful launch of Featherless AI this year.[00:02:20] AI Charlie: As always, don't forget to check the show notes for the YouTube link to their talk as well as their slides. Watch out and take care.[00:02:27] Intros[00:02:27] Dan Fu: Yeah, so thanks so much for having us. So this is going to be a little bit of a two part presentation. My name is Dan. I'm at Together AI, and I'll be joining UCSD as faculty in about a year. And Eugene, you want to introduce yourself?[00:02:46] Eugene Cheah: Eugene, I lead the art activity team, and I, I'm CEO of Featherless, and we both work on this new post transformer architecture space.[00:02:55] Dan Fu: Yeah, so yeah, so today we're really excited to talk to you a little bit [00:03:00] about that. So first I'm going to give a broad overview of kind of the last few years of progress in non post transformer architectures. And then afterwards Eugene will tell us a little bit about the latest and the greatest and the latest frontier models in this space.[00:03:16] Why Scale Context Lengths? or work on Efficient Models[00:03:16] Dan Fu: So, the story starts with Scaling. So this is probably a figure or something like this that you've seen very recently. Over the last five to six years, we've seen models really scale up in parameter size, and that's brought with it a bunch of new capabilities, like the ability to talk to you and tell you sometimes how to use your Colab screens.[00:03:35] Dan Fu: But another place where we've seen scaling especially recently is scaling in context length. So this can mean Having more text inputs for your models, but it can also mean things like taking a lot of visual token inputs image inputs to your models or generating lots of outputs. And one thing that's been really exciting over the last few months or so is that we're, we're seeing scaling, not only during training time, but also [00:04:00] during test time.[00:04:00] Dan Fu: So this is one of the, the, this is the iconic image from the OpenAI 01 release. Not only are we starting to scale train time compute, but we're also starting to scale test time compute. Now if you're familiar with our attention and our transformer architectures today, this graph on the right might look a little bit scary.[00:04:19] Dan Fu: And one of the reasons is that the implications are a little bit Interesting. So what does it mean if we want to continue having smarter and smarter models? Do we just need to start building bigger, bigger data centers, spending more flops? Is this this little Dolly 3, we need more flops, guys? Is this going to be the future of all of AI?[00:04:39] Dan Fu: Or is there a better way, another path forward? Maybe we can get the same capabilities that we've gotten used to, But for a lot less compute, a lot less flops. And one of the things that we're going to talk about today is specifically looking at that core attention operator in some of these models.[00:04:57] Dan Fu: And the reason is that so this is just some, some [00:05:00] basic you know, scaling curves, but attention has compute that scales quadratically in the context length. So that means that if you're doing something like test time compute and you want to spend a bunch of tokens thinking about what comes next, the longer that that goes the, the, the more tokens you spend on that, that compute grows quadratically in that.[00:05:19] Dan Fu: One of the questions that we're interested in is, can we take that basic sequence model, that basic sequence primitive at the bottom, and get it to scale better? Can we scale in, let's say, n to the 3 halves or n log n? So in, in the first part of the talk, so we just went over the introduction. What I'm gonna do over the next few slides is just talk about some of the key advances and ideas that have shown over the past few years since maybe early 2020 to, to now that shown promise that this might actually be possible.[00:05:48] Dan Fu: That you can actually get potentially the same quality that we want while scale, while scaling better. So to do that, we're and, and basically the, the story that we're gonna look is we're gonna start to see [00:06:00] how. So this is a basic graph of just the past couple years of progress of perplexity where that blue line, that dotted blue line, is attention.[00:06:07] The Story of SSMs[00:06:07] Dan Fu: It's your basic transformer, full dense attention. And then the dots coming down are some of the methods that you'll see in this presentation today. We're going to turn the clock back all the way to 2020. So this, this, this question of can we make attention subquadratic? Basically, as soon as we said attention is all you need, People started asking this question.[00:06:28] Dan Fu: So we have this quadratic attention operator. Can we do better? I'll briefly talk about why attention is quadratic. And the basic thing that happens, if you're not familiar, is that you have these inputs, these keys and queries. And what you do in this attention matrix, this S matrix over here, is that you're using, you're comparing every token in your input to every other token.[00:06:49] Dan Fu: So when I try to do something like upload a whole book to Gemini, what happens beyond the Maybe not Gemini, because we don't necessarily know what architecture is. But let's say we upload it to LLAMA, what happens beyond [00:07:00] the scenes, behind the scenes, is that it's going to take every single word in that book and compare it to every other word.[00:07:05] Dan Fu: And this has been a really, it's, it's led to some pretty impressive things. But it's kind of a brute forcing of the way that you would try to interpret a interpret something. And what attention does in particular is the, and then what attention, sorry, don't want to. Okay, no, no laser pointer. What, what attention does afterwards is that instead of always operating in this quadratic thing, it takes a row wise softmax over this matrix, and then multiplies it by this values matrix.[00:07:32] Dan Fu: So, one of the key points to notice is that the output size is always going to be the same as the inputs, at least in standard self attention. So one of the first things that folks tried to do around 2020 is this thing called linear attention, which is just, just noticing that if we take out this softmax from here, if we take out this non linearity in the middle of the attention operation, and then if you compute the keys and the values operation first, you actually never hit this quadratic bottleneck.[00:07:57] Dan Fu: So that, that's potentially a way [00:08:00] to get a lot more computationally efficient. And there are various ways to do this by basically using feature maps or try to approximate this overall attention computation. But some of this work sort of started to hit a wall in 2020. And the basic challenges were, were two.[00:08:16] Dan Fu: So one was quality. It was back then, it was kind of hard to, to get good quality with these linear attention operators. The other one was actually hardware efficiency. So these, this feature map that was just shown by a simplify simplify here. Actually ends up being quite computationally expensive if you just implement it naively.[00:08:34] Dan Fu: So you started having these operators that not only were you sure, you're not really sure if they have the same quality, but also they're actually just wall clock slower. So you kind of end up getting the worst of both worlds. So this was the the stage. So that kind of sets the stage for four years ago.[00:08:49] Dan Fu: Keep this in mind because linear attention is actually going to come back in a few years once we have a better understanding. But one of the works that started kicking off this, this [00:09:00] mini revolution in post transformer architectures was this idea called states based model. So here the seminal work is, is one about our work queue in 2022.[00:09:09] Dan Fu: And this, this piece of work really brought together a few ideas from, from some long running research research lines of work. The first one was, and this is really one of the keys to, to closing the gap in quality was just using things that, that if you talk to a, a, an electrical engineer off the street, they might know off, off the, like the back of their hand.[00:09:33] Idea 1: Approximation -> Principled Modeling[00:09:33] Dan Fu: But taking some of those properties with how we model dynamical systems in signal processing and then using those ideas to model the inputs, the, the text tokens in, for example a transformer like Next Token Prediction Architecture. So some of those early states-based model papers were looking at this relatively, relatively simple recurrent update model that comes from maybe chapter one of a signal processing class.[00:09:59] Dan Fu: But then using [00:10:00] some principle theory about how you should do that recurrent update in order to really get the most that you can out of your hidden state, out of your out of your sequence. So that, that was one key idea for quality and. When this was eventually realized, you started to see a bunch of benchmarks that were pretty sticky for a few years.[00:10:20] Dan Fu: Things like long range arena, some long sequence evaluation benchmarks, There was stuff in time series, time series analysis. They started to, you started to see the quality tick up in meaningful ways. But the other key thing that What's so influential about these states based models is that they also had a key idea about how you can compute these things efficiently.[00:10:45] Dan Fu: So if you go back to your machine learning 101 class where you learned about RNNs, one thing that you may have learned is that they don't paralyze as well as detention, because if you just run them naively, you have to do this kind of sequential update to process new tokens, [00:11:00] whereas in attention, you can process all the tokens in parallel at one time.[00:11:04] Dan Fu: One of the key insights behind the S4 paper was that these recurrent models, you could take them and you could also formulate them as a convolution. And in particular, with a convolution, you could, instead of using a PyTorch conv1d operation, you can compute that with the FFT. And that would give you n log n compute in the in the sequence length n with an operator that was relatively well optimized for modern hardware.[00:11:28] Dan Fu: So those are really, I'd say, the two key ideas in 2022 that started allowing these breakthroughs to happen in these non transformer architectures. So, these ideas about how to principally model sorry, how to model the recurrent updates of a mo of, of a sequence in a principled way, and also these key ideas in how you can compute it efficiently by turning it into a convolution and then scaling it up with the FFT.[00:11:53] Dan Fu: Along those same lines, so afterwards we started putting out some work on specialized kernels, so just [00:12:00] like we have flash attention for transformers, we also have works like flash fft conf, and if you look at these lines of work oftentimes when, whenever you see a new architecture, you see a new primitive one of the, one of the table stakes now is, do you have an efficient kernel so that you can actually get wall clock speed up?[00:12:14] Idea 3: Selection[00:12:14] Dan Fu: So by 2022, We are starting to have these models that had promising quality primitives, but and, and also promising wall clocks. So you could actually see regimes where they were better than transformers in meaningful ways. That being said, there were, there's still sometimes a quality gap, particularly for language modeling.[00:12:33] Dan Fu: And because languages, It's so core to what we do in sequence modeling these days the, the next, the next key idea that I'm going to talk about is this idea of selection mechanisms. And this is basically an idea of, so you have this recurrent state that you're keeping around that just summarizes everything that, that came before.[00:12:50] Dan Fu: And to get a good sequence model, one of the things that you really need to be able to do is have the model learn what's the best way to pick out pieces from that recurrent [00:13:00] state. So one of the, one of the major ideas here in a line of work called H3, Hungry Hungry Hippos, and also these hyena models were One way you can do this is by just adding some simple element wise gates.[00:13:13] Dan Fu: So versions of these ideas have been around for decades. If you squint at the LSTM paper you, you can probably find, find this gating mechanism. But turns out you can take those old ideas, add them into these new. state space models, and then you can see quality start to pick up. If you've heard of the Mamba model, this also takes the selection to the next level by actually making some changes in that fundamental recurrent state space.[00:13:40] Dan Fu: So, it's not only just this gating that happens around the SSM layer, but also you can actually make The ABCD matrices of your state space model, you can make them data dependent, which will allow you to even better select out different pieces from your hidden state depending on what you're seeing. I'll also point out if you look at the [00:14:00] bottom right of this figure, there's this little triangle with a GPU SRAM, GPU HBM, and this, this is just continuing that trend of when you have a new architecture you, you, you also release it with a kernel to, to, to show that it is hardware efficient, that it, that it can be hardware efficient on modern hardware.[00:14:17] Dan Fu: The, the, one of the next cool things that happened is once we had this understanding of these are the basic pieces, these are the basic principles behind some of the sequence models linear attention actually started to come back. So in earlier this year, there was a model called BASED the, from Simran Arora and, and some other folks, that combined a more principled version of linear attention that basically the, the, the, the two second summary is that it used a Taylor approximation of the softmax attention, combined that with a simple sliding window attention and was starting to able, starting to be able to expand the Pareto frontier of how much data can you recall from your sequence, versus how small is your recurrent state size.[00:14:58] Dan Fu: So those orange dots [00:15:00] are, at the top there, are just showing smaller sequences that can recall more memory.[00:15:07] Just Read Twice[00:15:07] Dan Fu: And the last major idea I think that has been influential in this line of work and is very relatively late breaking just a few months ago, is just the basic idea that when you have these models that are fundamentally more efficient in the sequence length, you maybe don't want to prompt them or use them in exactly the same way.[00:15:26] Dan Fu: So this was a really cool paper called Just Read Twice, also from Simran. That basically said, hey, all these efficient models can process tokens so much more efficiently than transformers that they can sometimes have unfair advantages compared to a simple transformer token. So, or sorry, a simple transformer model.[00:15:44] Dan Fu: So take, for example the standard, the standard use case of you have some long document, you're going to pass it in as input, and then you're going to ask some question about it. One problem you might imagine for a recurrent model where you have a fixed state size is, let's say that [00:16:00] you're. Article is very long, and you're trying to ask about some really niche thing.[00:16:04] Dan Fu: You can imagine it might be hard for the model to know ahead of time what information to put into the hidden state. But these, these, these models are so much more efficient that you can do something really stupid, like, you can just put the document write down the document, write down the question, write down the document again, and then write down the question again, and then this time, the second time that you go over that document, you know exactly what to look for.[00:16:25] Dan Fu: And the cool thing about this is, so this is, And this this results in better quality, especially on these recall intensive tasks. But the other interesting thing is it really takes advantage of the more efficient architectures that, that we're having here. So one of the other, I think, influential ideas in this line of work is if you change the fundamental compute capabilities of your model and the way that it scales, you can actually start to query it at test time differently.[00:16:51] Idea 4: Test Time Compute[00:16:51] Dan Fu: And this actually, of course, goes back to those slides on test time compute. So while everybody's looking at, say, test time compute for big transformer models, [00:17:00] I think potentially a really interesting research question is, how can you take those and how does it change with this new next generation of models?[00:17:09] Dan Fu: So the, I'll just briefly summarize what some of those key ideas were and then talk and then show you briefly kind of what the state of the art is today. So, so the four key ideas are instead of just doing a simple linear attention approximation, instead take ideas that we know from other fields like signal processing, do a more principled approach to your modeling of the sequence.[00:17:32] Idea 2: Hardware & Kernel Support[00:17:32] Dan Fu: Another key idea throughout all these lines of work is you really want. Hardware and kernel support from day one. So, so even if your model is theoretically more efficient if somebody goes and runs it and it's two times slower one of the things that, that we've learned is that if, if you're in that situation, it's, it's just gonna be dead on arrival.[00:17:49] Dan Fu: So you want to be designing your architectures one of the key, key machine learning ideas that has been important for the quality is just making sure that you encode different ways that you can [00:18:00] select from your hidden state and, and really focus on that as a key decider of quality. And finally, I think one of the, the, the emerging new, new things for, for this line of work and something that's quite interesting is, What are the right test time paradigms for these models?[00:18:15] Dan Fu: How do they change relative to relative to what you might do for a standard transformer? I'll briefly end this section. So I've labeled this slide where we are yesterday because Eugene is going to talk about some new models that he released literally this morning. But as of yesterday, some of the really cool results out of the, these efficient alternative models were so AI2 trained this hybrid MOE called Jamba.[00:18:40] Dan Fu: That, that, that seems, that is currently the state of the art for these non transformer architectures. There's this NVIDIA and MIT put out this new diffusion model called SANA recently that one of their key key observations is that you can take a standard diffusion transformer diffusion model, replace the layers with linear [00:19:00] attention, and then that lets you scale to much larger much larger images, much, much Much larger sequences more efficiently.[00:19:07] Dan Fu: And and one thing that I don't think anybody would have called when a few years ago is that one of those gated SSM, gated states based models ended up on the cover of Science because a great group of folks went and trained some DNA models. So that's Michael Polley, Eric Yuen from from Stanford and the Arc Institute.[00:19:26] Dan Fu: So it's, we're really at an exciting time in 2024 where these non transformer, post transformer architectures are showing promise across a wide range. Across a wide range of, of modalities, of applications, and, and of tasks. And with that, I'll pass it on to Eugene, who can tell you a little bit about the latest and greatest with RWKV.[00:19:49] RWKV vs SSMs[00:19:49] Eugene Cheah: So, that's useful? Yeah. You're talking to here. Oh, I'm talking to here. Okay. So, yeah, two streams. Yeah. So, I think one common questions that we tend to get asked, right, is what's the difference between [00:20:00] RWKV and state space? So I think one of the key things to really understand, right the difference between the two groups, right, is that we are actually more like an open source, random internet meets academia kind of situation.[00:20:11] Eugene Cheah: Like, most of us never wrote any paper, but we, we basically look at RNNs and linear intention when intention is all you need came out, and then we decided to like, hey there is a quadratic scaling problem. Why don't we try fixing that instead? So, so, so we end up developing our own branch, but we end up sharing ideas back and forth.[00:20:30] Eugene Cheah: So, and, and we do all this actively in Discord, GitHub, etc. This was so bad for a few years, right, that basically, the average group's H index was so close to zero, right, Illuter. ai actually came in and helped us write our first paper. Great, now our H index is now three, apparently. So, so, so, but, but the thing is, like, a lot of these experiments led to results, and, and, essentially, essentially, we we took the same ideas from linear attention, [00:21:00] and we built on it.[00:21:01] Eugene Cheah: So, to take a step back into, like, how does RWKB handle its own attention mechanic and achieve the same goals of, like, O and compute, respectively, and in focus of our overall goal to make AI accessible to everyone, regardless of language, nation, or compute, that's our goal. We actually train our models primarily on over a hundred languages, which is another topic altogether.[00:21:23] Eugene Cheah: And our goal is to train to even 200 languages to cover all languages in the world. But at the same time, we work on this architecture, To lower the compute cost so that people can run it on Raspberry Pis and on anything. So, how did RWKB break the dependency of LSTM token flow? Because I think to understand architecture, right, it's probably easier to understand it from the RNN lens.[00:21:46] Eugene Cheah: Because that's where we built on. We all, we all state space kind of like try to, try to start anew and took lessons from that and say, So there's a little bit of divergence there. And AKA, this our version of linear attention. So to take step back [00:22:00] all foundation models, be it transformers or non transformers at a very high level, right?[00:22:05] Eugene Cheah: Pumps in the token. I mean, text that things into embeddings and go through a lot of layers. Generate a lot of states where the QKV cache or be iron in states or RW KB states. And outputs and embedding, they are not the same thing. And we just take more layers and more embeddings. And somehow that magically works.[00:22:23] Eugene Cheah: So, if you, if you remember your ancient RNN lessons which we, which we, which we we call best learning these days the general idea is that you have the embedding information flowing all the way up, and when, and you take that information and you flow it back down, and then you process it as part of your LSTM layers.[00:22:41] Eugene Cheah: So, this is how it generally works. Kapati is quoted saying that RNNs are actually unreasonably effective. The problem is this is not scalable. To start doing work on the second token, you need to wait for the first token. And then you need to, and likewise for the third token and fourth token, yada yada.[00:22:55] Eugene Cheah: That is CPU land, not GPU land. So, so, so, you [00:23:00] can have a H100 and you can't even use 1 percent of it. So, so that's kind of why RNNs didn't really take off in the direction that we wanted, like, billions of parameters when it comes to training. So, what did RDAP KV version 0 do? Boom. We just did the dumbest, lamest thing.[00:23:13] Eugene Cheah: Sorry, this is the bottleneck for RNN. We did the dumb thing of removing that line. And it kind of worked. It trained. It sucked, but it kind of worked. Then we were like, hey, then no one cared because the loss was crap, but how do we improve that? And that's essentially where we move forward, because if you see this kind of flow, right, you can actually get your GPU saturated quickly, where it essentially cascades respectively.[00:23:41] Eugene Cheah: So I'm just waiting for this to loop again. So it's like, once you get your first layer, your token to be computed finish. You start to cascade your compute all the way until you are, Hey, I'm using 100 percent of the GPU. So we, we worked on it, and we started going along the principle of that as long as we keep this general architecture [00:24:00] where, where we can cascade and, and be highly efficient with our architecture, nothing is sacred in our architecture.[00:24:06] Eugene Cheah: And we have done some crazy ideas. In fact, you ask us, if you ask me to explain some things in the paper, right, officially in the paper, I'll say we had this idea and we wrote it this way. The reality is someone came with a code, we tested it, it worked, and then we rationalized later. So, so the general[00:24:24] RWKV Arch[00:24:24] Eugene Cheah: The idea behind rwkbr is that we generally have two major blocks that we do.[00:24:30] Eugene Cheah: We call time mix and channel mix. And time mix generally handles handles long term memory states, where essentially, where essentially where we apply the matrix multiplication and Cilu activation functions into processing an input embedding and an output embedding. I'm oversimplifying it because this, This calculation changed every version and we have, like, version 7 right now.[00:24:50] Eugene Cheah: ChannelMix is similar to Base in the sense that it does shorter term attention, where it just looks at the sister token, or the token before it, because [00:25:00] there's a shift in the token shift matrix. I don't really want to go too much into the papers itself, because, like, we do have three papers on this.[00:25:09] Eugene Cheah: Basically, RWKB, RNN for the transformer, ERA, Ego and Pinch, RWKB, Matrix Value State. This is the updated version 5, version 6. And Goldfinch is our, is, is, is, is our hybrid model respectively. We are writing the paper already for V seven and which is, which is for R wk V seven. Called, named Goose, or architectures are named by Bird.[00:25:30] Eugene Cheah: And, I'm going to cover as well, qrwkb, and mama100k, and rwkb, and Where did that lead to? Great! Because we are all GPU poor and to be clear, like, most of this research is done, like, only on a handful H100s, which I had one Google researcher told me that was, like, his experiment budget for a single researcher.[00:25:48] Eugene Cheah: So, our entire organization has less compute than a single researcher in Google. So We, we, one of the things that we explored into was to how do we convert transformer models instead? Because [00:26:00] someone already paid that billion dollars, a million dollars onto training, so why don't we take advantage of those weights?[00:26:05] Eugene Cheah: And, and to, I believe, together AI worked on the lockets for, for the Lambda side of things, and, and we took some ideas from there as well, and we essentially did that for RWKB.[00:26:15] QWRKWv6 launch[00:26:15] Eugene Cheah: And that led to, Q RWKB6, which we just dropped today, a 32 bit instruct preview model, where we took the Quen 32 bit instruct model, freeze the feedforward layer, remove the QKB attention layer, and replace it with RWKB linear layers.[00:26:32] Eugene Cheah: So to be clear, this means we do not have the rwkv channel mix layer, we only have the time mix layer. But but once we do that, we train the rwkv layer. Important is that the feedforward layer needs to be frozen, so the new attention can be learned. And then we unfreeze the feedforward layer, and train all the layers together with a custom learning rate schedule, so that they can learn how to work together.[00:26:54] Eugene Cheah: The end result, surprisingly, And, to be honest, to the frustration of the R. W. [00:27:00] KV MOE team, which ended up releasing the model on the same day, was that, with just a few hours of training on two nodes, we managed to get it to be on par, kind of, with the original QUAN32B model. So, in fact, when the first run, right, that completely confused us, it was like, and I was telling Daniel Goldstein, Smirky, who kind of leads most of our research coordination, When you pitched me this idea, you told me at best you'll get the same level of performance.[00:27:26] Eugene Cheah: You didn't tell me the challenge and score and Winograd score will shoot up. I don't know what's happening there. But it did. MMLU score dropping, that was expected. Because if you think about it, when we were training all the layers, right, we were essentially Like, Frankenstein this thing, and we did brain damage to the feedforward network layer 2 with the new RWKB layers.[00:27:47] Eugene Cheah: But, 76%, hey, somehow it's retained, and we can probably further train this. We didn't even spend more than 3 days training this, so there's a lot more that can be done, hence the preview. This brings up [00:28:00] a big question, because We are already now in the process of converting to 7TB. We are now, this is actually extremely compute efficient to test our attention mechanic.[00:28:10] Eugene Cheah: It's like, it becomes a shortcut. We can, we are already planning to do our version 7 and our hybrid architecture for it. Because we don't need to train from scratch. And we get a really good model out of it. And the other thing that is uncomfortable to say is that because we are doing right now on the 70b is that if this scales correctly to 128k context length, I'm not even talking about a million 128, majority of enterprise workload today is just on 70b at under 32k context length.[00:28:41] Eugene Cheah: That means if this works and the benchmark matches it, It means we can replace the vast majority of current AI workload, unless you want super long context. And then sorry, can someone give us more GPUs? Because we do need the VRAM for super long context, sadly. So yeah, that's what we are working on, and essentially, [00:29:00] we are excited about this to just push it further.[00:29:02] Eugene Cheah: And this conversion process, to be clear, I don't think it's going to be exclusive to RWKB. It probably will work for Mamba as well, I don't see why not. And we will probably see more ideas, or more experiments, or more hybrids, or Yeah, like, one of the weirdest things that I wanted to say outright, and I confirmed this with the Black Mamba team and the Jamba team, which because we did the GoFinch hybrid model, is that none of us understand why a hard hybrid with a state based model to be R.[00:29:28] Eugene Cheah: QA state space and transformer performs better when, than the baseline of both. It's like, it's like when you train one, you expect, and then you replace, you expect the same results. That's our pitch. That's our claim. But somehow when we jam both together, it outperforms both. And that's like one area of emulation that, like, we only have four experiments, plus four teams, that a lot more needs to be done.[00:29:51] Eugene Cheah: But, but these are things that excite me, essentially, because that is what it's potentially we can move ahead for. Which brings us to what comes next.[00:30:00] What's next[00:30:00] [00:30:00][00:30:00] Dan Fu: So, this part is kind of just some, where we'll talk a little bit about stuff that, that we're excited about. Maybe have some wild speculation on, on what, what's, what's coming next.[00:30:12] Dan Fu: And, of course this is also the part that will be more open to questions. So, a couple things that, that I'm excited about is continued hardware model co design for, for these models. So one of the things that we've put out recently is this library called ThunderKittens. It's a CUDA library.[00:30:29] Dan Fu: And one of the things that, that we found frustrating is every time that we built one of these new architectures, and I'm sure you had the exact same experience, we'd have to go and spend two months in CUDA land, like writing these, these new efficient things. And. If we decided to change one thing in PyTorch, like one line of PyTorch code is like a week of CUDA code at least.[00:30:47] Dan Fu: So one of our goals with, with a library like Thunderkitten, so we, we just broke down what are the key principles, what are the key hardware things what are the key, Compute pieces that you get from the hardware. So for example on [00:31:00] H100 everything is really revolves around a warp group matrix multiply operation.[00:31:06] Dan Fu: So you really want your operation to be able to split into relatively small matrix, matrix multiply operations. So like multiplying two 64 by 64 matrices, for example. And so if you know that ahead of time when you're designing your model, that probably gives you you know, some information about how you set the state sizes, how you set the update, how you set the update function.[00:31:27] Dan Fu: So with Thunderkittens we basically built a whole library just around this basic idea that all your basic compute primitives should not be a float, but it should be a matrix, and everything should just be matrix compute. And we've been using that to, to try to both re implement some existing architectures, and also start to design code.[00:31:44] Dan Fu: Some new ones that are really designed with this core with a tensor core primitive in mind. Another thing that that we're, that at least I'm excited about is we, over the last four or five years, we've really been looking at language models as the next thing. But if you've been paying [00:32:00] attention to Twitter there's been a bunch of new next generation models that are coming out.[00:32:04] Dan Fu: So there, there are. So, video generation models that can run real time, that are supported by your mouse and your keyboard, that I'm told if you play with them that, you know, that they only have a few seconds of memory. Can we take that model, can we give it a very long context length so that you could actually maybe generate an entire game state at a time?[00:32:25] Dan Fu: What does that look like for the model? You're certainly not going to do a giant quadratic attention computation to try to run that. Maybe, maybe use some of these new models, or some of these new video generation models that came out. So Sora came out I don't know, two days ago now. But with super long queue times and super long generation times.[00:32:43] Dan Fu: So that's probably a quadratic attention operation at the, at the bottom of it. What if we could remove that and get the same quality, but a lot faster generation time? Or some of the demos that we saw from Paige earlier today. You know, if I have a super long conversation with my [00:33:00] Gemini bot, what if I wanted to remember everything that it's seen in the last week?[00:33:06] Dan Fu: I mean, maybe you don't for personal reasons, but what if I did, you know? What does that mean for the architecture? And I think, you know, that's certainly something I'm pretty excited about. I'm sure you're excited about it too. So, I think we were supposed to have some hot takes, but I honestly don't remember what our hot takes were.[00:33:21] Hot Takes - does anyone really need long context?[00:33:21] Eugene Cheah: Yeah, including the next slide. Hot takes, yes, these are our[00:33:25] Dan Fu: hot takes.[00:33:25] Eugene Cheah: I think the big one on Twitter that we saw, that we shared, was the question is like, is RAG relevant? In the case of, like, the future of, like, state based models?[00:33:38] Dan Fu: Let's see, I haven't played too much with RAG. But when I have. I'll say I found it was a little bit challenging to do research on it because we had this experience over and over again, where you could have any, an embedding model of any quality, so you could have a really, really bad embedding model, or you could have a really, really [00:34:00] good one, By any measure of good.[00:34:03] Dan Fu: And for the final RAG application, it kind of didn't matter. That's what I'll say about RAG while I'm being recorded. I know it doesn't actually answer the question, but[00:34:13] Eugene Cheah: Yeah, so I think a lot of folks are like, extremely excited of the idea of RWKB or State Space potentially having infinite context.[00:34:21] Eugene Cheah: But I think the reality is that when we say infinite context, we just mean a different kind of infinite context, or you, or as it's previously covered, you need to test the model differently. So, think of it more along the lines of the human. Like, I don't remember what I ate for breakfast yesterday.[00:34:37] Eugene Cheah: Yeah, that's the statement that I'll say. And And we humans are not quadratic transformers. If we did, if let's say we increased our brain size for every second we live, we would have exploded by the time we are 5 years old or something like that. And, and I think, I think basically fundamentally for us, right, be it whether we, regardless of whether RWKB, statespace, XLSTM, [00:35:00] etc, our general idea is that instead of that expanding state, that increase in computational cost, what if we have a fixed state size?[00:35:08] Eugene Cheah: And Information theory detects that that fixed state size will have a limit. Just how big of a limit is a question, like, we, like, RWKB is running at 40 megabytes for, for its state. Its future version might run into 400 megabytes. That is like millions of tokens in, if you're talking about mathematically, the maximum possibility.[00:35:29] Eugene Cheah: It's just that I guess we were all more inefficient about it, so maybe we hit 100, 000. And that's kind of like the work we are doing, trying to like push it and maximize it. And that's where the models will start differing, because it will choose to forget things, it will choose to remember things. And that's why I think that there might be some element of right, but it may not be the same right.[00:35:49] Eugene Cheah: It may be the model learn things, and it's like, hmm, I can't remember that, that article. Let me do a database search, to search. Just like us humans, when we can't remember the article in the company. We do a search on Notion. [00:36:00][00:36:00] Dan Fu: I think something that would be really interesting is if you could have facts that are, so right now, the one intuition about language models is that all those parameters are around just to store random facts about the world.[00:36:14] Dan Fu: And this intuition comes from the observation that if you take a really small language model, it can do things like talk to you, or kind of has like the The style of conversation, it can learn that, but where it will usually fall over compared to a much larger one is it'll just be a lot less factual about things that it knows or that it can do.[00:36:32] Dan Fu: But that points to all those weights that we're spending, all that SGD that we're spending to train these models are just being used to store facts. And we have things like databases that are pretty good at storing facts. So I think one thing that would be really interesting is if we could actually have some sort of outside data store that a language model can can look at that that maybe is you know, has has some sort of gradient descent in it, but but would be quite interesting.[00:36:58] Dan Fu: And then maybe you could edit it, delete [00:37:00] facts, you know, change who's president so that it doesn't, it doesn't get lost.[00:37:04] Vibhu: Can we open up Q& A and hot takes for the audience? I have a hot take Q& A. Do these scale? When, when 405B state space model, RAG exists, no one does long context, who's throwing in 2 million token questions, hot takes?[00:37:24] Dan Fu: The, the who's throwing in 2 million token question, I think, is, is a really good question. So I actually, I was going to offer that as a hot take. I mean, my hot take was going to be that long context doesn't matter. I know I just gave a whole talk about it, but you know, what, what's the point of doing research if you can't, you know, play both sides.[00:37:40] Dan Fu: But I think one of the, so I think for both of us, the reason that we first got into this was just from the first principled questions of there's this quadratic thing. Clearly intelligence doesn't need to be quadratic. What is going on? Can we understand it better? You know, since then it's kind of turned into a race, which has [00:38:00] been exciting to watch, like, how much context you can take in.[00:38:03] Dan Fu: But I think it's right. Nobody is actually putting in a two million context prompt into these models. And, and, you know, if they are, maybe we can go, go You know, design a better model to do that particular thing. Yeah, what do you think about that? So you've also been working on this. Do you think long context matters?[00:38:19] Eugene Cheah: So I'm going to burn a bit. How many of you remember the news of Google Gemini supporting 3 million contacts, right? Raise your hand.[00:38:28] Vibhu: Yeah, 2 million.[00:38:29] Eugene Cheah: Oh, it's 2 million.[00:38:31] Eugene Cheah: Yeah, how many of you actually tried that? See?[00:38:34] Vibhu: I use it a lot. You? You work for MindsTV. I use it a lot.[00:38:41] Eugene Cheah: So, for some people that has used, and I think, I think that's the, that's might be, like, this is where my opinion starts to differ, because I think the big labs may have a bigger role in this, because Like, even for RWKB, even when we train non contacts, the reason why I say VRAM is a problem is that because when we did the, we need to backprop [00:39:00] against the states, we actually need to maintain the state in between the tokens by the token length.[00:39:05] Eugene Cheah: So that means we need to actually roll out the whole 1 million contacts if we are actually training 1 million. Which is the same for transformers, actually, but it just means we don't magically reuse the VRAM consumption in the training time space. So that is one of the VRAM bottlenecks, and I'm neither OpenAI nor Google, so donate GPUs if you have too much of them.[00:39:27] Eugene Cheah: But then, putting it back to another paradigm, right, is that I think O1 style reasoning might be actually pushing that direction downwards. In my opinion, this is my partial hot take is that if, let's say you have a super big model, And let's say you have a 70B model that may take double the tokens, but gets the same result.[00:39:51] Eugene Cheah: Strictly speaking, a 70B, and this is even for transformer or non transformer, right? We we'll take less less resources than that 400 B [00:40:00] model, even if it did double the amount thinking. And if that's the case, and we are still all trying to figure this out, maybe the direction for us is really getting the sub 200 B to be as fast as efficient as possible.[00:40:11] Eugene Cheah: We a very efficient architecture that some folks happen to be working on to, to just reason it out over larger and larger context thing.[00:40:20] Question: Yeah. One thing I'm super interested in is. Models that can watch forever? Obviously you cannot train something on infinite context length. How are y'all thinking about that, where you run on a much longer context length than is possible to train on?[00:40:38] Dan Fu: Yeah, it's a, it's a great question. So I think when I think you guys probably had tweets along these lines, too. When we first started doing these things, because these are all recurrent models in theory you could just run it forever. You could just run it forever. And at the very least it won't, it won't like error out on your crash.[00:40:57] Dan Fu: There's another question of whether it can actually [00:41:00] use what it's seen in that infinite context. And I think there, so one place where probably the research and architectures ran faster Then another research is actually the benchmarks for long context. So you turn it on forever. You want to do everything or watch everything.[00:41:16] Dan Fu: What is it that you actually wanted to do? Can we actually build some benchmarks for that? Then measure what's happening. And then ask the question, can the models do it? Is there something else that they need? Yeah, I think that if I were to turn back the clock to 2022, that's probably one of the things I would have done differently, which would have been actually get some long context benchmarks out at the same time as we started pushing context length on all these models.[00:41:41] Eugene Cheah: I will also say the use case. So like, I think we both agree that there's no Infinite memory and the model needs to be able to learn and decide. I think what we have observed for, I think this also fits the state space model, is that one of the key advantages of this alternate attention mechanic that is not based on token position is that the model don't suddenly become crazy when you go past the [00:42:00] 8k training context tank, or a million context tank.[00:42:03] Eugene Cheah: It's actually still stable. It's still able to run, it's still able to rationalize. It just starts forgetting things. But some of these things are still there in latent memory. Some of these things are still somewhat there. That's the whole point of why reading twice works. Things like that. And one of the biggest pushes in this direction is that I think both Statespace and RWKB have Separate papers by other researchers where they use this architecture for time series data.[00:42:26] Eugene Cheah: Weather modeling. So, you are not asking what was the weather five days ago. You're asking what's the weather tomorrow based on the infinite length that we, as long as this Earth and the computer will keep running. So, so, and they found that it is like, better than existing, like, transformer or existing architecture in modeling this weather data.[00:42:47] Eugene Cheah: Control for the param size and stuff. I'm quite sure there are people with larger models. So, so there are things that, that in this case, right, there is future applications if your question is just what's next and not what's 10 years ago.[00:42:59] Dan Fu: Thanks so [00:43:00] much for having us. Get full access to Latent Space at www.latent.space/subscribe

This week's reading from the Torah, parsha Vayazhev (Genesis/Bereshiet chapters 37 through 40) shifts the story of the line of the patriarchs to Yosef/Joseph, the first-born son of Rachel. The Bible tells us there was favoritism, and that is just part of the reason his brothers resented him. The Erev Shabbat reading covers that beginning, and his sale into slavery in Egypt, the house of Potiphar, and then prison. There is far more, too: https://hebrewnationonline.com/wp-content/uploads/2024/12/SSM-12-20-24-Vayashev-teaching-podcast-xx.mp3 There are a number of major themes in the study of Joseph this week, from what he teaches us about dreams, to that issue of favoritism and jealousy, and the results, to a larger question about 'adversity', and how it figures in our lives, and His plan. But in the middle of all that is one of the most notable "chiasms," (Mark prefers the Hebrew term 'atbash' - for "alef-tav, beit-shin" because the first and last, and second and second-to-last name is so descriptive of the Biblical equivalent of an HTML tag)) in the Bible: about Judah and Tamar. That theme, of what happens "in-between" resonates. Because we, today, are there too: Vayashev: The Time 'In-Between' https://hebrewnationonline.com/wp-content/uploads/2024/12/WT-CooH-12-21-24-Vayashev-Josephs-time-In-Between-xx.mp3 The combined two-part teaching is here:

This week's parsha, Vayishlach (Genesis/Bereshiet 32:4 thru chapter 36) continues the story of Yakov/Jacob at the time where he has left the house of Laban, and begins the return to his hom, as commanded. And, importantly, that story begins with his encounter with his long-estranged brother Esau, who, as he last recalled, intended to kill him. The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2024/12/SSM-12-13-24-Vayishlach-teaching-podcast-x.mp3 The Sabbath Day midrash includes a look at the prophet Obadiah, and asks a question. Or is it clear? Vayishlach: Esau is Edom...is...AmeriKa???" Means! https://hebrewnationonline.com/wp-content/uploads/2024/12/WT-CooH-12-14-24-Vayishlach-Esau-is-Edom-is-AmeriKa-xx.mp3 The combined two-part teaching is here:

This week's parsha, Vayetze (Genesis/Bereshiet 25:19-32:3) follows the story of Yakov/Jacob after he leaves home and heads to the place of his mother Rivka/Rebeccah's family. And like so many things concerning the Patriarchs, it is not only maximally Politically NOT-Correct, but practically a litmus test for how far so much of the sun-god-day church has departed from the lessons of Scripture. The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2024/12/SSM-12-6-24-Vayetze-teaching-podcast-xx.mp3 There is a whole lot that much of 'xtianity' really doesn't like about this one. And for the same reasons, some of the context may even seem confusing to 'modern sensitivities.' Why, for example, is the man who lied to his father to "usurp" his elder brother Esau's blessing, and birthright, also held up as an icon of "emet," the Hebrew word for 'truth'? And why would the Creator of the Universe and Author of Scripture choose to use a man with four wives to bring forth His people? Is it possible that there's something in this story that 'the Church' would prefer to overlook, or outright hide? This story is not merely NOT-PC. It's a glaring example of what so pervades the world that so hates His Word today: Vayetze: Real vs Fake" Means! https://hebrewnationonline.com/wp-content/uploads/2024/12/WT-CooH-12-7-24-Vayetze-Fake-vs-real-the-NOT-PC-Salvation-of-YHVH-podcast-xxx.mp3 The combined two-part teaching is here:

Join Mark Call of Shabbat Shalom Mesa fellowship for a two-part look at this week's parsha, Toldot (Genesis/Bereshiet 25:19-28:9) which is the primary description in the Bible of the life of Yitzak/Isaac, and includes the stories of his twin sons, Esau and Yakov. The Erev Shabbat reading: https://hebrewnationonline.com/wp-content/uploads/2024/11/SSM-11-29-24-Toldot-teaching-podcast-xx.mp3 The Sabbath Day midrash is focused on what was originally called a "struggle" in the womb between the two twin brothers. But the Hebrew word used (ratzatz), and Rivkah's reaction, suggest it was FAR more intense than a mere struggle. And it continues, in every way. Because so does the reason that Esau is "hated" by YHVH. Toldot: Poor Esau? Or the 'Battle Has Never Ended?' https://hebrewnationonline.com/wp-content/uploads/2024/11/CooH-11-29-24-Toldot-Poor-Esau-the-Continuing-Struggle-er-RAGE-podcast-xx.mp3 The combined two-part teaching is here:

This week's parsha, Chayei Sarah (Genesis/Bereshiet 23:1 - 25:18) essentially concludes the story of the life of the Patriarch, Abraham, but is titled the 'Life of Sarah,' and begins with her death at the age of 127. But this portion is perhaps THE most significant exposition of principles once known as the English Common Law in all of Scripture, by example. The Erev Shabbat reading, from the First Land Contract, to the First "Good and Faithful Servant," and a prototype for what constitutes marriage as well: https://hebrewnationonline.com/wp-content/uploads/2024/11/SSM-11-22-24-Chayei-Sarah-teaching-podcast-xx.mp3 Mark Call of Shabbat Shalom Mesa has noted that it is surprising (but perhaps shouldn't be!) how often the regular Torah parsha reading is so precisely on-target for what it happening in the world at that time. This one seems to be an exception. At least until we look a bit deepeer. What does a parsha that has EVERYTHING to do with fundamental elements of the 'common law' matter in a week where the big issue seems to be whether the world even survives long enough for an inauguration? The answer is in the contrast: we got here because "lawlessness abounds," and not only has the "love of many grown cold," but outright hatred seems to abound as well in its place. Chayei Sarah: A message for the Remnant - who had better know what "Come in His Name" Means! https://hebrewnationonline.com/wp-content/uploads/2024/11/WT-CooH-11-24-24-Chayei-Sarah-Talking-to-the-Remnant-in-the-Name-of-podcast-xx.mp3 The combined two-part teaching is here:

This week's parsha, Vayeira (Genesis/Bereshiet chapters 18 through 22) tells the second part of the story of the life of the Patriarch, Abraham, and includes at least two of the most well-known, and even prophetic, incidents in that sage. The parsha title, Vayeira, "And He appeared," refers to YHVH Himself, and two of His 'malakim,' or messengers, who appeared to Abraham on the eve of the destruction of Sodom and Gomorrah, and is the time when the patriarch famously 'dickers' with the Creator on behalf of those about to die. And there is more to that visit as well. The Erev Shabbat reading concludes with perhaps the famous event in his life, which is certainly not only prophetic, and foreshadowing, but also cited as the epitome of an "act of faith": https://hebrewnationonline.com/wp-content/uploads/2024/11/SSM-11-15-24-Vayeira-teaching-podcast-xx.mp3 The Sabbath Day midrash is all about a question that Mark Call suggests is something we should be considering today: Can WE have "faith like Abraham?' After all, this patriarch is essentially not only the 'Father of Our Faith,' but also a man who faith is literally of "Biblical Proportions." There are other factors to consider... ...but we can, and must. Vayeira: The 'Faith' of Abraham' - and what it means for us https://hebrewnationonline.com/wp-content/uploads/2024/11/WT-CooH-11-16-24-Vayeira-Trust-and-Faith-like-Abraham-podcast-xxx.mp3 The combined two-part teaching is here:

Join Mark Call of Shabbat Shalom Mesa fellowship this week for a two-part look at the first parsha chronicling the life of THE Patriarch, Abraham. The Erev Shabbat reading begins with the title phrase, Lekh lekha, or "get thee out," of your land, your home, everything you've known, and go to the place that "I will show you." He just does so, in an act of faith that has stood as a testament to that faith for millenia: https://hebrewnationonline.com/wp-content/uploads/2024/11/SSM-11-8-24-Lekh-Lekha-teaching-podcast-xx.mp3 And, again, there is much in the life of this first patriarch that is so fundamental, so important, and so long-forgotten now, that it amounts to an object lesson about what is wrong with a society which is so clueless about THE fundamental structure of society, and government. It should be no surprise, then, that so much of what Abraham did, and represented, is anathema to a 'church' that prefers its own dogma to His Written Word. From marriage, to 'works', to circumcision - there are lessons here that have been twisted, or worse. The Sabbath Day midrash asks a question that Mark suggests MUST be asked at "such a time as this," now that the 'Date Certain' has passed, but the danger, and the challenges ahead, have only begun. Do we understand why "the world" so DESPISES everything about "patriarchy". And why, if we are to "return to Him," it starts with understanding what the father Abraham teaches us? Lekh Lekha: Abraham, THE Patriarch, Which Matters NOW - because Some of the Blessings Come First https://hebrewnationonline.com/wp-content/uploads/2024/11/WT-CooH-11-8-24-Lekh-Lekha-Patriarchy-NOW-Some-of-the-Blessings-Come-First-podcast-xxx.mp3 The combined two-part teaching is here:

We began the reading of Parsha Noach last week, both with the story of his genealogy, the nature of the world at that time, and the Flood itself. But that parsha also includes at least one other famous story, and one which also bears more relevance today that we might like to admit. The Erev Shabbat reading of the parsha follows the Flood, in chapters ten 12 of Bereshiet/Genesis, and includes the story of Nimrod, and the Tower of Babel: https://hebrewnationonline.com/wp-content/uploads/2024/11/SSM-10-18-24-Noach-pt-2-Babylon-n-Nimrod-teaching-podcast-x.mp3 The Sabbath Day midrash picks up the theme of Nimrod, Babel, and what it was about that tower that was so unique to YHVH that it merited the response He gave it. And it seems to have lot to do with what Bebylon became, and evidently still represents: a system that is antagonistic to His. There are parallels, anti-parallels, but this time the question concerns what might follow the parallels after that Flood, "as it was in the days of Noach..." The issue this time is Babylon, and what constitutes the 'Greater Babylon Metro Area.' Noach+: Nimrod, Babylong and 'Transformational Technology' The Remnant must Self-Select! https://hebrewnationonline.com/wp-content/uploads/2024/11/WT-CooH-11-2-24-Noach-pt-2-Nimrod-Babylon-and-Transformatnl-Tech-REMNANT-must-Self-Select-podcast-xx.mp3 The combined two-part teaching is here:

In some ways, Bereshiet (Genesis, and "in the Beginning) is the most fundamental element in the Bible. Literally everything else builds, line-by-line, precept-by-precept, upon that Foundation. Mark Call of Shabbat Shalom Mesa fellowship has often contended, that six chapters of Genesis in parsha Bereshiet (Genesis 1 through 6) is just too much to even try to do justice to, study-wise, in a single week, So, this cycle, we depart a bit from the "annual Torah reading" layout to do a bit deeper dive into this second half of the first parsha in the Book. Which actually 'overlaps' via the story of Noach, the Nephilim, and the Flood anyway. The Erev Shabbat reading of the 'next segment', into the story of Noach and the Flood, in chapters four through 9 of Bereshiet/Genesis: https://hebrewnationonline.com/wp-content/uploads/2024/10/SSM-10-25-24-Bereshiet-thru-Noach-special-teaching-podcast-xx.mp3 The Sabbath Day midrash is about Big, even "climactic" changes. And there are two that follow the logical sequence of the story: Noach, and the Flood, and - don't forget - the Book of Joshua describes the events AFTER the five Books of the Torah, and the conquest of The Land. And that, too, was a time of Big Changes. Which is true today. And there are parallels, anti-parallels, and no shortage of warnings about what looks like "as it was in the days of Noach..." Bereshiet+: Big, BIG Changes - both Then and Now https://hebrewnationonline.com/wp-content/uploads/2024/10/WT-CooH-10-26-24-Bereshiet-thru-Noach-special-Big-Changes-Know-the-Season-podcast-xx.mp3 The combined two-part teaching is here:

Socal Seasoning paid SSM a visit while HSD was traveling for work.  After they banged, they sent HSD some hot videos, then put on the headsets and recoded this episode!   ...and for those wondering: yes, they banged again afterwards. A recap of our really hot MFM and the spanking benchOur Hawaii trip (and the after Hawaii fun..)Some of your questions answered about SoCal!Find a lot more of SoCal Seasoning here: https://linktr.ee/socalseasoningSupport the showVisit https://linktr.ee/sexxxysoccermom to see lots more of Sexxxy Soccer Mom

After nearly 700 years, one of the most important Western magical compendiums in history has been fully translated into English for the first time. The Summa Sacre Magice (SSM) is a 200,000 word Latin manuscript written in 1346 by Catalan magician Berengarii Gannellii, and is considered the most in-depth overview of Latin medieval magic ever. In a stunning achievement, scholar, author and Solomonic practitioner Dr. Stephen Skinner, along with co-author and researcher Daniel Clark, is presenting Volume One of their translation of all five books of the SSM into English. We are honored as Dr. Skinner returns on Glitch Bottle to go deep into this incredible work. ⇓ ⇓ ⇓► ✅(Amazon USA) Pre-order ‘Summa Sacre Magice' - https://www.amazon.com/dp/0738781231/ ► ✅(Amazon UK) - Pre-order ‘Summa Sacre Magice 'https://www.amazon.co.uk/Summa-Sacre-Magice-Compendium-Sourcewords/dp/191221248X/ ► ✅Golden Hoard Press - https://goldenhoard.net/index.htm✦