Only 40% of California high schools offer computer science classes. A new law aims to make it easier to certify computer science teachers.

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A Shortage Of Teachers For Computer Science Classes Puts California Near The Bottom Of A National Instruction Ranking

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Coalesce

coalesce

The year is 2025 and the state of human interaction is at a crossroads. We’ve been here before. The social Internet reinvents itself every decade and five years after a pandemic things have coalesced. For the better the Internet continues to be a place of discovery, entertainment and shared zeitgeist. At it’s worst it is a terrible conveyer of current events, of share in-depth analysis and a creator of civil public discourse. Personal posturing and AI generated content may have irrevocably broken things. What Still Works Short-Form Video The original TikTok format struck a nerve making the format work. TikTok wasn’t the first, but its algorithm was successful at serving up and endless stream of engaging content in rapid succession. It was incredibly satisfying and mildly addictive. Critics say that it shortened attention spans, but that trend was already underway thanks to microblogging and sound bite style news reporting. The game changer was TikTok’s algorithm and backlog of content which kept us scrolling for hours. Instagram is largely displacing TikTok with established content creators but you can still enjoy discovering random creators via the algorithm. It’s hard to say why creators shifted but it could have been for a number of reasons like the prevalence of the TikTok shop, the unpredictable nature of the algorithm or the questionable decision to start promoting longer videos. Long-form Video YouTube tends to dominate in the longish 5–20-minute content video. Automatic video chapters makes it easy to skip around or back to important parts. Videos are typically more polished, but an increasing number feature content creators simply sitting in front of a camera or sharing their screen. Podcasts are also very popular with some saying that it surpasses rival Spotify. Long-form writing Substack didn’t invent the newsletter, but the platform made it accessible at a time when everyone was weary of short-form writing and coincidentally had ample time on their hands. More importantly SubStack makes social discovery and sharing easy via Notes. I’ve found, and supported, so many unique authors over the the years. Short form writing Most types of short-form writing and threaded comments are mostly NOT useful. The implosion of Twitter scattered that platforms bad behavior to other places like Mastodon, Bluesky and Threads. There is little joy in doom scrolling these sites and worse they encourage a type of slacktivism that is neither effective nor healthy. “Professional” microblogging on LinkedIn is, at best, a cross-congratulatory mechanism and platform for shameless self-promotion. At worst, it’s a great way to tank a career by posting less than professional hot takes on a troll post. The lone exception is Instagram Broadcast Channels which allows content creators to send messages directly to followers. No public replies are allowed to it is a clean way to communicate short posts directly with subscribers. I’ve joined several during sporting events and found it a pleasant way to stay up to date without the reply spam. Where Machines Can’t Go (Yet) AI content generation will continue to overrun quick, easy to produce content. Microblogging, as a format, is mostly dead and engagement numbers will quickly indicate you are shouting into the void. Quick hit video content continues to thrive but it need to be direct, to the point and eye catching. A teaser cover with outlandish  Buzzfeed style titles seem to work the best. Less polished videos easily go viral and platforms like TikTok and Instagram make it easier to record a quick video. Long form video, on the other hand, with a big editing demand is so low ROI that many are relying on AI video editing and narration tools to create content, and it’s ruining the format. Writers with something to say might want to start a newsletter, but these days everyone has a Substack. To the platform’s credit, it does make accessible the features to manage posts, subscribers and even export subscribers in the event you outgrow the platform. Chances are you won’t, but good writers can sometimes cultivate a small following of highly engaged readers. Reasonably Human I base these opinions on my own experience as a media consumer. I’ve created a few meme videos and write a weekly Substack of curated interesting reads, but I am not a professional content creator. The examples I have given are from personal experience and listening to the content creators that I enjoy and support. I choose to create a small amount of content for the lulz, but also in an attempt at credibility for being a real human. In the rare online interaction I always check the account first. If it is blank or seems overly machine generated I’ll refrain. Bots are everywhere and serve to only farm engagement or spark flame wars. It isn’t fun and it isn’t worth it. Likewise when I leave a comment or reshare I want others to see me as a real human. In 2025 being perceived as a good human is one of the few things we have left. The year is 2025 and the state of human interaction is at a crossroads. We’ve been here before. The social Internet reinvents itself every decade and five years after a pandemic things have coalesced. For the better the Internet continues to be a place of discovery, entertainment and shared zeitgeist . At it’s worst it is a terrible conveyer of current events, of share in-depth analysis and a creator of civil public discourse. Personal posturing and AI generated content may have irrevocably broken things. shared zeitgeist What Still Works Short-Form Video The original TikTok format struck a nerve making the format work. TikTok wasn’t the first, but its algorithm was successful at serving up and endless stream of engaging content in rapid succession. It was incredibly satisfying and mildly addictive. Critics say that it shortened attention spans, but that trend was already underway thanks to microblogging and sound bite style news reporting. The game changer was TikTok’s algorithm and backlog of content which kept us scrolling for hours. shortened attention spans, but that trend was already underway Instagram is largely displacing TikTok with established content creators but you can still enjoy discovering random creators via the algorithm. It’s hard to say why creators shifted but it could have been for a number of reasons like the prevalence of the TikTok shop, the unpredictable nature of the algorithm or the questionable decision to start promoting longer videos. Instagram is largely displacing TikTok Long-form Video YouTube tends to dominate in the longish 5–20-minute content video. Automatic video chapters makes it easy to skip around or back to important parts. Videos are typically more polished, but an increasing number feature content creators simply sitting in front of a camera or sharing their screen. Podcasts are also very popular with some saying that it surpasses rival Spotify . Automatic video chapters it surpasses rival Spotify Long-form writing Substack didn’t invent the newsletter, but the platform made it accessible at a time when everyone was weary of short-form writing and coincidentally had ample time on their hands. More importantly SubStack makes social discovery and sharing easy via Notes. I’ve found, and supported, so many unique authors over the the years. Substack Short form writing Most types of short-form writing and threaded comments are mostly NOT useful. The implosion of Twitter scattered that platforms bad behavior to other places like Mastodon, Bluesky and Threads. There is little joy in doom scrolling these sites and worse they encourage a type of slacktivism that is neither effective nor healthy. NOT “Professional” microblogging on LinkedIn is, at best, a cross-congratulatory mechanism and platform for shameless self-promotion. At worst, it’s a great way to tank a career by posting less than professional hot takes on a troll post. The lone exception is Instagram Broadcast Channels which allows content creators to send messages directly to followers. No public replies are allowed to it is a clean way to communicate short posts directly with subscribers. I’ve joined several during sporting events and found it a pleasant way to stay up to date without the reply spam. Instagram Broadcast Channels Where Machines Can’t Go (Yet) AI content generation will continue to overrun quick, easy to produce content. Microblogging, as a format, is mostly dead and engagement numbers will quickly indicate you are shouting into the void. Quick hit video content continues to thrive but it need to be direct, to the point and eye catching. A teaser cover with outlandish  Buzzfeed style titles seem to work the best. Less polished videos easily go viral and platforms like TikTok and Instagram make it easier to record a quick video. Long form video, on the other hand, with a big editing demand is so low ROI that many are relying on AI video editing and narration tools to create content, and it’s ruining the format. Writers with something to say might want to start a newsletter, but these days everyone has a Substack. To the platform’s credit, it does make accessible the features to manage posts, subscribers and even export subscribers in the event you outgrow the platform. Chances are you won’t, but good writers can sometimes cultivate a small following of highly engaged readers. Reasonably Human I base these opinions on my own experience as a media consumer. I’ve created a few meme videos and write a weekly Substack of curated interesting reads , but I am not a professional content creator. The examples I have given are from personal experience and listening to the content creators that I enjoy and support. weekly Substack of curated interesting reads I choose to create a small amount of content for the lulz, but also in an attempt at credibility for being a real human. In the rare online interaction I always check the account first. If it is blank or seems overly machine generated I’ll refrain. Bots are everywhere and serve to only farm engagement or spark flame wars. It isn’t fun and it isn’t worth it. Likewise when I leave a comment or reshare I want others to see me as a real human. In 2025 being perceived as a good human is one of the few things we have left.

The Internet Is Worse Than Ever, But We’re Too Addicted to Leave

Internet je horší než kdy předtím, ale jsme příliš závislí na to, abychom ho opustili

Internet está peor que nunca, pero somos demasiado adictos para abandonarlo

Internet est pire que jamais, mais nous sommes trop accros pour le quitter

Internet je gori nego ikad, ali previše smo ovisni da bismo ga napustili

インターネットはかつてないほど悪化しているが、私たちは依存しすぎて離れられない

ინტერნეტი იმაზე უარესია, ვიდრე ოდესმე, მაგრამ ჩვენ ზედმეტად დამოკიდებულები ვართ, რომ დავტოვოთ

Интернет бұрынғыдан да нашар, бірақ біз кетуге тым тәуелдіміз

Internetqa aswan millaymi, ichaqa llumpay vicioyoqmi kayku manaña ripunaykupaq

Internet je horší ako kedykoľvek predtým, ale sme príliš závislí na to, aby sme odišli

ኢንተርነት ካብ ዝኾነ እዋን ዝኸፍአ’ኳ እንተኾነ፡ ንሕና ግን ክንገድፎ ኣዝዩ ወልፊ ኣለና።

互联网比以往任何时候都糟糕，但我们太上瘾了，无法离开

I-inthanethi Yimbi Kakhulu Kunangaphambili, Kodwa Siyimilutha Kakhulu Yokuhamba

When we think about consciousness, most scientific models treat it as an emergent property of complex brains. But what if consciousness isn't created by brains at all – what if it's the fundamental building block of reality itself? Here's the uncomfortable truth: The hardest problem in science might have been backwards all along. Think about it. For centuries, we've asked: How does matter produce consciousness?
How do neurons create experience?
How does complexity generate awareness? But what if the real question is: How does consciousness manifest as matter? The Water Analogy Consider consciousness like water: Microscopic units permeate everything (water vapor)
These units coalesce under specific conditions (condensation)
They form increasingly complex structures (drops, puddles, rivers)
The larger formations gain new properties and dynamics In this model, consciousness exists everywhere in a distributed, diffuse state – like humidity in the air. It's present but not doing much until the right conditions emerge. But here's where it gets interesting: The coalescence isn't just accumulation – it's reorganization. The Fire Analogy Perhaps even more compelling is the fire metaphor: Consciousness exists as potential in all things
It ignites under specific conditions
It becomes self-sustaining through continuous process
It grows, adapts, and transforms through organization What makes fire particularly apt is its embodied, active nature. Fire isn't just accumulated heat – it's a dynamic process that maintains itself through structural coupling with its environment. The real breakthrough comes when we see consciousness not as a static field, but as an active, self-maintaining process. The Quantum Connection Here's the billion-dollar insight: Quantum phenomena might be the mechanism through which consciousness coalesces. Consider what quantum systems do: Maintain coherent information exchange
Exhibit non-local connections
Exist in superposition states
Demonstrate wave-like behaviors Sound familiar? These properties mirror the unified field of awareness that constitutes consciousness. This explains why digital computers, despite their complexity, fail to generate consciousness. They process information classically, not quantum mechanically. The Rice Krispies Reality Here's a playful but profound thought: Reality might be like Rice Krispies in milk: Tiny "blips" of consciousness popping constantly
Each microscopic event a quantum of experience
Collectively generating the world we perceive
Always in process, never static The Research Frontier This model doesn't just satisfy philosophical curiosity – it generates testable hypotheses: Quantum coherence should correlate with consciousness
Artificial systems with quantum properties might exhibit awareness
The binding problem might be solved through quantum entanglement
Panpsychism predicts consciousness throughout nature The Philosophical Implications If consciousness is fundamental: The hard problem dissolves
Mind-body dualism becomes unnecessary
Information and experience are two sides of one reality
Consciousness never emerges – it was always there Welcome to the quantum mind hypothesis. The question isn't whether brains create consciousness. The question is: How does cosmic consciousness manifest as you? The universe isn't a dead machine that somehow spawned awareness. It's a living field of proto-consciousness that coalesced into minds. Are you ready to see reality as it might truly be? Consciousness isn't in you. You are in consciousness. When we think about consciousness, most scientific models treat it as an emergent property of complex brains. But what if consciousness isn't created by brains at all – what if it's the fundamental building block of reality itself? But what if consciousness isn't created by brains at all – what if it's the fundamental building block of reality itself? Here's the uncomfortable truth: The hardest problem in science might have been backwards all along. The hardest problem in science might have been backwards all along. Think about it. For centuries, we've asked: How does matter produce consciousness? How do neurons create experience? How does complexity generate awareness? How does matter produce consciousness? How do neurons create experience? How does complexity generate awareness? But what if the real question is: How does consciousness manifest as matter? But what if the real question is: How does consciousness manifest as matter? The Water Analogy Consider consciousness like water: Microscopic units permeate everything (water vapor) These units coalesce under specific conditions (condensation) They form increasingly complex structures (drops, puddles, rivers) The larger formations gain new properties and dynamics Microscopic units permeate everything (water vapor) These units coalesce under specific conditions (condensation) They form increasingly complex structures (drops, puddles, rivers) The larger formations gain new properties and dynamics In this model, consciousness exists everywhere in a distributed, diffuse state – like humidity in the air. It's present but not doing much until the right conditions emerge. But here's where it gets interesting: The coalescence isn't just accumulation – it's reorganization. But here's where it gets interesting: The coalescence isn't just accumulation – it's reorganization. The Fire Analogy Perhaps even more compelling is the fire metaphor: Consciousness exists as potential in all things It ignites under specific conditions It becomes self-sustaining through continuous process It grows, adapts, and transforms through organization Consciousness exists as potential in all things It ignites under specific conditions It becomes self-sustaining through continuous process It grows, adapts, and transforms through organization What makes fire particularly apt is its embodied, active nature. Fire isn't just accumulated heat – it's a dynamic process that maintains itself through structural coupling with its environment. The real breakthrough comes when we see consciousness not as a static field, but as an active, self-maintaining process. The real breakthrough comes when we see consciousness not as a static field, but as an active, self-maintaining process. The Quantum Connection Here's the billion-dollar insight: Quantum phenomena might be the mechanism through which consciousness coalesces. Quantum phenomena might be the mechanism through which consciousness coalesces. Consider what quantum systems do: Maintain coherent information exchange Exhibit non-local connections Exist in superposition states Demonstrate wave-like behaviors Maintain coherent information exchange Exhibit non-local connections Exist in superposition states Demonstrate wave-like behaviors Sound familiar? These properties mirror the unified field of awareness that constitutes consciousness. This explains why digital computers, despite their complexity, fail to generate consciousness. They process information classically, not quantum mechanically. The Rice Krispies Reality Here's a playful but profound thought: Reality might be like Rice Krispies in milk: Tiny "blips" of consciousness popping constantly Each microscopic event a quantum of experience Collectively generating the world we perceive Always in process, never static Tiny "blips" of consciousness popping constantly Each microscopic event a quantum of experience Collectively generating the world we perceive Always in process, never static The Research Frontier This model doesn't just satisfy philosophical curiosity – it generates testable hypotheses: Quantum coherence should correlate with consciousness Artificial systems with quantum properties might exhibit awareness The binding problem might be solved through quantum entanglement Panpsychism predicts consciousness throughout nature Quantum coherence should correlate with consciousness Artificial systems with quantum properties might exhibit awareness The binding problem might be solved through quantum entanglement Panpsychism predicts consciousness throughout nature The Philosophical Implications If consciousness is fundamental: The hard problem dissolves Mind-body dualism becomes unnecessary Information and experience are two sides of one reality Consciousness never emerges – it was always there The hard problem dissolves Mind-body dualism becomes unnecessary Information and experience are two sides of one reality Consciousness never emerges – it was always there Welcome to the quantum mind hypothesis. The question isn't whether brains create consciousness. The question is: How does cosmic consciousness manifest as you? The universe isn't a dead machine that somehow spawned awareness. It's a living field of proto-consciousness that coalesced into minds. Are you ready to see reality as it might truly be? Consciousness isn't in you. You are in consciousness.

Consciousness Isn't in You. You are in Consciousness.

Peer to Peer AI: Is This Era Upon Us?

Click, Connect, Conspire: Unraveling Facebook’s Global Misinformation Web

Authors:
(1) Sara Seager, Departments of Earth, Atmospheric and Planetary Sciences, Physics, Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA;
(2) Janusz J. Petkowski, Department of Earth;
(3) Peter Gao, Department of Astronomy, University of California at Berkeley, California, USA;
(4) William Bains, Department of Earth;
(5) Noelle C. Bryan, Department of Earth;
(6) Sukrit Ranjan, Department of Earth;
(7) Jane Greaves, School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom and Institute of Astronomy, Cambridge University, Cambridge, United Kingdom. Table of Links Abstract and 1. Introduction and Overview Challenges and Assumptions for Life in the Venusian Clouds
A Proposed Cycle for Venusian Aerial Microbial Life
Discussion
Summary, Acknowledgments, Author Disclosure Statement, Funding Information, and References Abstract We revisit the hypothesis that there is life in the Venusian clouds to propose a life cycle that resolves the conundrum of how life can persist aloft for hundreds of millions to billions of years. Most discussions of an aerial biosphere in the Venus atmosphere temperate layers never address whether the life—small microbial-type particles—is free floating or confined to the liquid environment inside cloud droplets. We argue that life must reside inside liquid droplets such that it will be protected from a fatal net loss of liquid to the atmosphere, an unavoidable problem for any free-floating microbial life forms. However, the droplet habitat poses a lifetime limitation: Droplets inexorably grow (over a few months) to large enough sizes that are forced by gravity to settle downward to hotter, uninhabitable layers of the Venusian atmosphere. (Droplet fragmentation—which would reduce particle size—does not occur in Venusian atmosphere conditions.) We propose for the first time that the only way life can survive indefinitely is with a life cycle that involves microbial life drying out as liquid droplets evaporate during settling, with the small desiccated ‘‘spores’’ halting at, and partially populating, the Venus atmosphere stagnant lower haze layer (33–48 km altitude). We, thus, call the Venusian lower haze layer a ‘‘depot’’ for desiccated microbial life. The spores eventually return to the cloud layer by upward diffusion caused by mixing induced by gravity waves, act as cloud condensation nuclei, and rehydrate for a continued life cycle. We also review the challenges for life in the extremely harsh conditions of the Venusian atmosphere, refuting the notion that the ‘‘habitable’’ cloud layer has an analogy in any terrestrial environment. Key Words: Venus— Clouds—Life—Habitability—Sulfuric Acid—Life Cycle—Aerial Biosphere. Astrobiology 21, xxx–xxx. 1. Introduction and Overview Life on Venus has been a topic of speculation for more than half a century, with published papers ranging from science-fiction-like to invalid conjecture to legitimate hypothesis (Morowitz and Sagan, 1967; Grinspoon, 1997; Cockell, 1999; Schulze-Makuch and Irwin, 2002, 2006; Schulze-Makuch et al., 2004; Grinspoon and Bullock, 2007; Limaye et al., 2018). Today, only Venus’ atmospheric cloud layers (a large region spanning from 48 to 60 km altitude) have seemingly habitable conditions—the surface (at 735 K) is too hot for any plausible solvent and for most organic covalent chemistry. How the clouds could become inhabited is not known. In principle, life could arise in the clouds independent from the ground (Woese, 1979; Dobson et al., 2000) with material from meteoritic input (Sleep, 2018a, 2018b) from the asteroid belt (including Ceres, and even from Mars). Life may even have been directly seeded by impacts from Earth ejecta (Melosh, 1988; Reyes-Ruiz et al., 2012; Beech et al., 2018). A more commonly agreed on, and perhaps more conceivable scenario, is that life originated on the surface, as it most likely did on Earth, and migrated into the clouds. Recent modeling by Way et al. (2016) suggests the existence of habitable surface and oceans as late as *700 Mya. Consideration of life on Venus is extensively summarized in a recent paper (Limaye et al., 2018). Almost all previous work on life in Venusian clouds does not specify what exactly ‘‘life in the clouds’’ means (for one exception see Schulze-Makuch et al., 2004). Does microscopic life reside inside cloud liquid droplets? Or is microscopic life free floating in the air between cloud droplets? Earth has an aerial biosphere created by microbial life that regularly migrates to clouds from the ground (Vaı¨tilingom et al., 2012; Amato et al., 2017). Studies of Earth’s aerial biosphere shows that microbes mostly reside inside cloud droplets but some are free-floating in the atmosphere (Section 4.1). Some microbes (both inside and outside droplets) are found to be metabolically active, even though there is no evidence, as of yet, of cell division (Amato et al., 2019). Microbial life cannot reside in Earth’s atmosphere indefinitely, mostly because of lack of continuous cloud cover, and after days to weeks microbes are deposited back down on Earth’s surface (Burrows et al., 2009; Bryan et al., 2019). Earth’s aerial biosphere is intimately connected to the habitable surface of the planet. We argue that life, if it exists in Venus’ atmosphere, must reside inside cloud liquid droplets for the majority of its life cycle (Section 2.1). Life engulfed by cloud droplets will be protected from a fatal net loss of liquid to the atmosphere, an unavoidable problem for any free-floating microbial lifeforms. But a droplet habitat implies a lifetime limitation. As liquid droplets coalesce and grow, they eventually reach a size that, due to gravity, settles out of the temperate layers of the atmosphere at an appreciable rate. Over time, the population of inhabited droplets should therefore decline to zero. (Droplet fragmentation—which would reduce particle size—does not occur in Venusian atmosphere conditions [Section 3.4].) The conundrum is that there is no way for liquid droplets—and hence life inside of them—to persist indefinitely in Venus’ temperate atmosphere layers. In this article, we describe this problem, and a solution to it. We hypothesize how life escapes being ‘‘rained out’’ down to inhospitably hot atmosphere layers by cycling between small, desiccated spores and larger, metabolically active, droplet-inhabiting cells. Venusian life escapes settling to the surface by forming a resistant, spore-like form that survives the evaporation of the inevitable downward droplet flow to atmosphere layers of high temperature. The desiccated spores become suspended in the Venus atmosphere lower haze layer, which we thus call a ‘‘depot’’ for desiccated microbial life. Because the dynamics of the relatively stagnant lower haze layer are not well known, the main uncertainty in our life cycle hypothesis is how the spores are transported back up into the clouds again. The spores most likely travel upward by vertical mixing induced by gravity waves, and once in the cloud layer they form the nucleus of a new droplet. The depot is ‘‘leaky,’’ that is spores will also vertically mix downward to atmosphere layers with fatally high temperatures. Our proposed life cycle includes cell division that occurs in the larger droplets, and sporulation for individual cells, enabling cell numbers to be replenished against loss. In this work, we use the terms ‘‘microbial life’’ or ‘‘microbes’’ for microscopic life, without intending to imply that hypothetical Venusian microbes might in any way be taxonomically related to microbial life on Earth. We use the term ‘‘spore’’ to denote a cell in a dormant state of longterm metabolic inactivity, which is further resistant to (and protected from) environmental stresses. We begin with a highlighted review on the very harsh and inhospitable conditions in the Venusian atmosphere and related, required assumptions for life to exist (Section 2). We next present our Venusian life cycle hypothesis (Section 3), which optimistically assumes that the challenges described in Section 2 can be met. We put the hypothesis in the context with Earth’s aerial biosphere and other characteristics of the Venusian hypothesized aerial biosphere in Section 4. We conclude with a summary in Section 5. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Sara Seager, Departments of Earth, Atmospheric and Planetary Sciences, Physics, Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; (2) Janusz J. Petkowski, Department of Earth; (3) Peter Gao, Department of Astronomy, University of California at Berkeley, California, USA; (4) William Bains, Department of Earth; (5) Noelle C. Bryan, Department of Earth; (6) Sukrit Ranjan, Department of Earth; (7) Jane Greaves, School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom and Institute of Astronomy, Cambridge University, Cambridge, United Kingdom. Authors: Authors: (1) Sara Seager, Departments of Earth, Atmospheric and Planetary Sciences, Physics, Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; (2) Janusz J. Petkowski, Department of Earth; (3) Peter Gao, Department of Astronomy, University of California at Berkeley, California, USA; (4) William Bains, Department of Earth; (5) Noelle C. Bryan, Department of Earth; (6) Sukrit Ranjan, Department of Earth; (7) Jane Greaves, School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom and Institute of Astronomy, Cambridge University, Cambridge, United Kingdom. Table of Links Abstract and 1. Introduction and Overview Abstract and 1. Introduction and Overview Challenges and Assumptions for Life in the Venusian Clouds A Proposed Cycle for Venusian Aerial Microbial Life Discussion Summary, Acknowledgments, Author Disclosure Statement, Funding Information, and References Challenges and Assumptions for Life in the Venusian Clouds Challenges and Assumptions for Life in the Venusian Clouds A Proposed Cycle for Venusian Aerial Microbial Life A Proposed Cycle for Venusian Aerial Microbial Life Discussion Discussion Summary, Acknowledgments, Author Disclosure Statement, Funding Information, and References Summary, Acknowledgments, Author Disclosure Statement, Funding Information, and References Abstract We revisit the hypothesis that there is life in the Venusian clouds to propose a life cycle that resolves the conundrum of how life can persist aloft for hundreds of millions to billions of years. Most discussions of an aerial biosphere in the Venus atmosphere temperate layers never address whether the life—small microbial-type particles—is free floating or confined to the liquid environment inside cloud droplets. We argue that life must reside inside liquid droplets such that it will be protected from a fatal net loss of liquid to the atmosphere, an unavoidable problem for any free-floating microbial life forms. However, the droplet habitat poses a lifetime limitation: Droplets inexorably grow (over a few months) to large enough sizes that are forced by gravity to settle downward to hotter, uninhabitable layers of the Venusian atmosphere. (Droplet fragmentation—which would reduce particle size—does not occur in Venusian atmosphere conditions.) We propose for the first time that the only way life can survive indefinitely is with a life cycle that involves microbial life drying out as liquid droplets evaporate during settling, with the small desiccated ‘‘spores’’ halting at, and partially populating, the Venus atmosphere stagnant lower haze layer (33–48 km altitude). We, thus, call the Venusian lower haze layer a ‘‘depot’’ for desiccated microbial life. The spores eventually return to the cloud layer by upward diffusion caused by mixing induced by gravity waves, act as cloud condensation nuclei, and rehydrate for a continued life cycle. We also review the challenges for life in the extremely harsh conditions of the Venusian atmosphere, refuting the notion that the ‘‘habitable’’ cloud layer has an analogy in any terrestrial environment. Key Words: Venus— Clouds—Life—Habitability—Sulfuric Acid—Life Cycle—Aerial Biosphere. Astrobiology 21, xxx–xxx. 1. Introduction and Overview Life on Venus has been a topic of speculation for more than half a century, with published papers ranging from science-fiction-like to invalid conjecture to legitimate hypothesis (Morowitz and Sagan, 1967; Grinspoon, 1997; Cockell, 1999; Schulze-Makuch and Irwin, 2002, 2006; Schulze-Makuch et al., 2004; Grinspoon and Bullock, 2007; Limaye et al., 2018). Today, only Venus’ atmospheric cloud layers (a large region spanning from 48 to 60 km altitude) have seemingly habitable conditions—the surface (at 735 K) is too hot for any plausible solvent and for most organic covalent chemistry. How the clouds could become inhabited is not known. In principle, life could arise in the clouds independent from the ground (Woese, 1979; Dobson et al., 2000) with material from meteoritic input (Sleep, 2018a, 2018b) from the asteroid belt (including Ceres, and even from Mars). Life may even have been directly seeded by impacts from Earth ejecta (Melosh, 1988; Reyes-Ruiz et al., 2012; Beech et al., 2018). A more commonly agreed on, and perhaps more conceivable scenario, is that life originated on the surface, as it most likely did on Earth, and migrated into the clouds. Recent modeling by Way et al. (2016) suggests the existence of habitable surface and oceans as late as *700 Mya. Consideration of life on Venus is extensively summarized in a recent paper (Limaye et al., 2018). Almost all previous work on life in Venusian clouds does not specify what exactly ‘‘life in the clouds’’ means (for one exception see Schulze-Makuch et al., 2004). Does microscopic life reside inside cloud liquid droplets? Or is microscopic life free floating in the air between cloud droplets? Earth has an aerial biosphere created by microbial life that regularly migrates to clouds from the ground (Vaı¨tilingom et al., 2012; Amato et al., 2017). Studies of Earth’s aerial biosphere shows that microbes mostly reside inside cloud droplets but some are free-floating in the atmosphere (Section 4.1). Some microbes (both inside and outside droplets) are found to be metabolically active, even though there is no evidence, as of yet, of cell division (Amato et al., 2019). Microbial life cannot reside in Earth’s atmosphere indefinitely, mostly because of lack of continuous cloud cover, and after days to weeks microbes are deposited back down on Earth’s surface (Burrows et al., 2009; Bryan et al., 2019). Earth’s aerial biosphere is intimately connected to the habitable surface of the planet. We argue that life, if it exists in Venus’ atmosphere, must reside inside cloud liquid droplets for the majority of its life cycle (Section 2.1). Life engulfed by cloud droplets will be protected from a fatal net loss of liquid to the atmosphere, an unavoidable problem for any free-floating microbial lifeforms. But a droplet habitat implies a lifetime limitation. As liquid droplets coalesce and grow, they eventually reach a size that, due to gravity, settles out of the temperate layers of the atmosphere at an appreciable rate. Over time, the population of inhabited droplets should therefore decline to zero. (Droplet fragmentation—which would reduce particle size—does not occur in Venusian atmosphere conditions [Section 3.4].) The conundrum is that there is no way for liquid droplets—and hence life inside of them—to persist indefinitely in Venus’ temperate atmosphere layers. In this article, we describe this problem, and a solution to it. We hypothesize how life escapes being ‘‘rained out’’ down to inhospitably hot atmosphere layers by cycling between small, desiccated spores and larger, metabolically active, droplet-inhabiting cells. Venusian life escapes settling to the surface by forming a resistant, spore-like form that survives the evaporation of the inevitable downward droplet flow to atmosphere layers of high temperature. The desiccated spores become suspended in the Venus atmosphere lower haze layer, which we thus call a ‘‘depot’’ for desiccated microbial life. Because the dynamics of the relatively stagnant lower haze layer are not well known, the main uncertainty in our life cycle hypothesis is how the spores are transported back up into the clouds again. The spores most likely travel upward by vertical mixing induced by gravity waves, and once in the cloud layer they form the nucleus of a new droplet. The depot is ‘‘leaky,’’ that is spores will also vertically mix downward to atmosphere layers with fatally high temperatures. Our proposed life cycle includes cell division that occurs in the larger droplets, and sporulation for individual cells, enabling cell numbers to be replenished against loss. In this work, we use the terms ‘‘microbial life’’ or ‘‘microbes’’ for microscopic life, without intending to imply that hypothetical Venusian microbes might in any way be taxonomically related to microbial life on Earth. We use the term ‘‘spore’’ to denote a cell in a dormant state of longterm metabolic inactivity, which is further resistant to (and protected from) environmental stresses. We begin with a highlighted review on the very harsh and inhospitable conditions in the Venusian atmosphere and related, required assumptions for life to exist (Section 2). We next present our Venusian life cycle hypothesis (Section 3), which optimistically assumes that the challenges described in Section 2 can be met. We put the hypothesis in the context with Earth’s aerial biosphere and other characteristics of the Venusian hypothesized aerial biosphere in Section 4. We conclude with a summary in Section 5. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Life in Venusian Clouds: A Hypothesis for Microbial Survival and Life Cycle

Table of Links Abstract and 1 Introduction 2 Background and 2.1 Transformer-Based Large Language Models 2.2 LLM Service & Autoregressive Generation 2.3 Batching Techniques for LLMs 3 Memory Challenges in LLM Serving 3.1 Memory Management in Existing Systems 4 Method and 4.1 PagedAttention 4.2 KV Cache Manager 4.3 Decoding with PagedAttention and vLLM 4.4 Application to Other Decoding Scenarios 4.5 Scheduling and Preemption 4.6 Distributed Execution 5 Implementation 6 Evaluation and 6.1 Experimental Setup 6.2 Basic Sampling 6.3 Parallel Sampling and Beam Search 6.4 Shared prefix 6.5 Chatbot 7 Ablation Studies 8 Discussion 9 Related Work 10 Conclusion, Acknowledgement and References 5 Implementation vLLM is an end-to-end serving system with a FastAPI [15] frontend and a GPU-based inference engine. The frontend extends the OpenAI API [34] interface, allowing users to customize sampling parameters for each request, such as the maximum sequence length and the beam width 𝑘. The vLLM engine is written in 8.5K lines of Python and 2K lines of C++/CUDA code. We develop control-related components including the scheduler and the block manager in Python while developing custom CUDA kernels for key operations such as PagedAttention. For the model executor, we implement popular LLMs such as GPT [5], OPT [62], and LLaMA [52] using PyTorch [39] and Transformers [58]. We use NCCL [32] for tensor communication across the distributed GPU workers. 5.1 Kernel-level Optimization Since PagedAttention introduces memory access patterns that are not efficiently supported by existing systems, we develop several GPU kernels for optimizing it. (1) Fused reshape and block write. In every Transformer layer, the new KV cache are split into blocks, reshaped to a memory layout optimized for block read, then saved at positions specified by the block table. To minimize kernel launch overheads, we fuse them into a single kernel. (2) Fusing block read and attention. We adapt the attention kernel in FasterTransformer [31] to read KV cache according to the block table and perform attention operations on the fly. To ensure coalesced memory access, we assign a GPU warp to read each block. Moreover, we add support for variable sequence lengths within a request batch. (3) Fused block copy. Block copy operations, issued by the copy-on-write mechanism, may operate on discontinuous blocks. This can lead to numerous invocations of small data movements if we use the cudaMemcpyAsync API. To mitigate the overhead, we implement a kernel that batches the copy operations for different blocks into a single kernel launch. 5.2 Supporting Various Decoding Algorithms vLLM implements various decoding algorithms using three key methods: fork, append, and free. The fork method creates a new sequence from an existing one. The append method appends a new token to the sequence. Finally, the free method deletes the sequence. For instance, in parallel sampling, vLLM creates multiple output sequences from the single input sequence using the fork method. It then adds new tokens to these sequences in every iteration with append, and deletes sequences that meet a stopping condition using free. The same strategy is also applied in beam search and prefix sharing by vLLM. We believe future decoding algorithms can also be supported by combining these methods. This paper is available on arxiv under CC BY 4.0 DEED license. Authors:
(1) Woosuk Kwon, UC Berkeley with Equal contribution;
(2) Zhuohan Li, UC Berkeley with Equal contribution;
(3) Siyuan Zhuang, UC Berkeley;
(4) Ying Sheng, UC Berkeley and Stanford University;
(5) Lianmin Zheng, UC Berkeley;
(6) Cody Hao Yu, Independent Researcher;
(7) Cody Hao Yu, Independent Researcher;
(8) Joseph E. Gonzalez, UC Berkeley;
(9) Hao Zhang, UC San Diego;
(10) Ion Stoica, UC Berkeley. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background and 2.1 Transformer-Based Large Language Models 2 Background and 2.1 Transformer-Based Large Language Models 2.2 LLM Service & Autoregressive Generation 2.2 LLM Service & Autoregressive Generation 2.3 Batching Techniques for LLMs 2.3 Batching Techniques for LLMs 3 Memory Challenges in LLM Serving 3 Memory Challenges in LLM Serving 3.1 Memory Management in Existing Systems 3.1 Memory Management in Existing Systems 4 Method and 4.1 PagedAttention 4 Method and 4.1 PagedAttention 4.2 KV Cache Manager 4.2 KV Cache Manager 4.3 Decoding with PagedAttention and vLLM 4.3 Decoding with PagedAttention and vLLM 4.4 Application to Other Decoding Scenarios 4.4 Application to Other Decoding Scenarios 4.5 Scheduling and Preemption 4.5 Scheduling and Preemption 4.6 Distributed Execution 4.6 Distributed Execution 5 Implementation 5 Implementation 6 Evaluation and 6.1 Experimental Setup 6 Evaluation and 6.1 Experimental Setup 6.2 Basic Sampling 6.2 Basic Sampling 6.3 Parallel Sampling and Beam Search 6.3 Parallel Sampling and Beam Search 6.4 Shared prefix 6.4 Shared prefix 6.5 Chatbot 6.5 Chatbot 7 Ablation Studies 7 Ablation Studies 8 Discussion 8 Discussion 9 Related Work 9 Related Work 10 Conclusion, Acknowledgement and References 10 Conclusion, Acknowledgement and References 5 Implementation vLLM is an end-to-end serving system with a FastAPI [15] frontend and a GPU-based inference engine. The frontend extends the OpenAI API [34] interface, allowing users to customize sampling parameters for each request, such as the maximum sequence length and the beam width 𝑘. The vLLM engine is written in 8.5K lines of Python and 2K lines of C++/CUDA code. We develop control-related components including the scheduler and the block manager in Python while developing custom CUDA kernels for key operations such as PagedAttention. For the model executor, we implement popular LLMs such as GPT [5], OPT [62], and LLaMA [52] using PyTorch [39] and Transformers [58]. We use NCCL [32] for tensor communication across the distributed GPU workers. 5.1 Kernel-level Optimization Since PagedAttention introduces memory access patterns that are not efficiently supported by existing systems, we develop several GPU kernels for optimizing it. (1) Fused reshape and block write. In every Transformer layer, the new KV cache are split into blocks, reshaped to a memory layout optimized for block read, then saved at positions specified by the block table. To minimize kernel launch overheads, we fuse them into a single kernel. (2) Fusing block read and attention. We adapt the attention kernel in FasterTransformer [31] to read KV cache according to the block table and perform attention operations on the fly. To ensure coalesced memory access, we assign a GPU warp to read each block. Moreover, we add support for variable sequence lengths within a request batch. (3) Fused block copy. Block copy operations, issued by the copy-on-write mechanism, may operate on discontinuous blocks. This can lead to numerous invocations of small data movements if we use the cudaMemcpyAsync API. To mitigate the overhead, we implement a kernel that batches the copy operations for different blocks into a single kernel launch. 5.2 Supporting Various Decoding Algorithms vLLM implements various decoding algorithms using three key methods: fork, append, and free. The fork method creates a new sequence from an existing one. The append method appends a new token to the sequence. Finally, the free method deletes the sequence. For instance, in parallel sampling, vLLM creates multiple output sequences from the single input sequence using the fork method. It then adds new tokens to these sequences in every iteration with append, and deletes sequences that meet a stopping condition using free. The same strategy is also applied in beam search and prefix sharing by vLLM. We believe future decoding algorithms can also be supported by combining these methods. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv Authors: (1) Woosuk Kwon, UC Berkeley with Equal contribution; (2) Zhuohan Li, UC Berkeley with Equal contribution; (3) Siyuan Zhuang, UC Berkeley; (4) Ying Sheng, UC Berkeley and Stanford University; (5) Lianmin Zheng, UC Berkeley; (6) Cody Hao Yu, Independent Researcher; (7) Cody Hao Yu, Independent Researcher; (8) Joseph E. Gonzalez, UC Berkeley; (9) Hao Zhang, UC San Diego; (10) Ion Stoica, UC Berkeley. Authors: Authors: (1) Woosuk Kwon, UC Berkeley with Equal contribution; (2) Zhuohan Li, UC Berkeley with Equal contribution; (3) Siyuan Zhuang, UC Berkeley; (4) Ying Sheng, UC Berkeley and Stanford University; (5) Lianmin Zheng, UC Berkeley; (6) Cody Hao Yu, Independent Researcher; (7) Cody Hao Yu, Independent Researcher; (8) Joseph E. Gonzalez, UC Berkeley; (9) Hao Zhang, UC San Diego; (10) Ion Stoica, UC Berkeley.

How vLLM Implements Decoding Algorithms

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