Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio.

This is part three of: Yudkowsky and Christiano discuss "Takeoff Speeds", published by Eliezer Yudkowsky on The AI Alignment Forum.

5.8. TPUs and GPUs, and automating AI R&D

[Yudkowsky][23:17]

I'm also wondering a little why the emphasis on "trillions". it seems to me that the terms of your Prophecy should be fulfillable by AGI tech being merely as ubiquitous as modern computers, so that many competing companies invest mere hundreds of billions in the equivalent of hardware plants. it is legitimately hard to get a chip with 50% better transistors ahead of TSMC.

[Christiano][23:17]

yes, if you are investing hundreds of billions then it is hard to pull ahead (though could still happen)

(since the upside is so much larger here, no one cares that much about getting ahead of TSMC since the payoff is tiny in the scheme of the amounts we are discussing)

[Yudkowsky][23:18]

which, like, doesn't prevent Google from tossing out TPUs that are pretty significant jumps on GPUs, and if there's a specialized application of AGI-ish tech that is especially key, you can have everything behave smoothly and still get a jump that way.

[Christiano][23:18]

I think TPUs are basically the same as GPUs

probably a bit worse

(but GPUs are sold at a 10x markup since that's the size of nvidia's lead)

[Yudkowsky][23:19]

noted; I'm not enough of an expert to directly contradict that statement about TPUs from my own knowledge.

[Christiano][23:19]

(though I think TPUs are nevertheless leased at a slightly higher price than GPUs)

[Yudkowsky][23:19]

how does Nvidia maintain that lead and 10x markup? that sounds like a pretty un-Paul-ish state of affairs given Bitcoin prices never mind AI investments.

[Christiano][23:20]

nvidia's lead isn't worth that much because historically they didn't sell many gpus

(especially for non-gaming applications)

their R&D investment is relatively large compared to the $ on the table

my guess is that their lead doesn't stick, as evidenced by e.g. Google very quickly catching up

[Yudkowsky][23:21]

parenthetically, does this mean - and I don't necessarily predict otherwise - that you predict a drop in Nvidia's stock and a drop in GPU prices in the next couple of years?

[Christiano][23:21]

nvidia's stock may do OK from riding general AI boom, but I do predict a relative fall in nvidia compared to other AI-exposed companies

(though I also predicted google to more aggressively try to compete with nvidia for the ML market and think I was just wrong about that, though I don't really know any details of the area)

I do expect the cost of compute to fall over the coming years as nvidia's markup gets eroded

to be partially offset by increases in the cost of the underlying silicon (though that's still bad news for nvidia)

[Yudkowsky][23:23]

I parenthetically note that I think the Wise Reader should be justly impressed by predictions that come true about relative stock price changes, even if Eliezer has not explicitly contradicted those predictions before they come true. there are bets you can win without my having to bet against you.

[Christiano][23:23]

you are welcome to counterpredict, but no saying in retrospect that reality proved you right if you don't 🙂

otherwise it's just me vs the market

[Yudkowsky][23:24]

I don't feel like I have a counterprediction here, but I think the Wise Reader should be impressed if you win vs. the market.

however, this does require you to name in advance a few "other AI-exposed companies".

[Christiano][23:25]

Note that I made the same bet over the last year---I make a large AI bet but mostly moved my nvidia allocation to semiconductor companies. The semiconductor part of the portfolio is up 50% while nvidia is up 70%, so I lost that one. But that just means I like the bet even more next year.

happy to use nvidia vs tsmc

[Yudkowsky][23:25]

there's a lot of noise ...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio.

This is part three of: Yudkowsky and Christiano discuss "Takeoff Speeds", published by Eliezer Yudkowsky on The AI Alignment Forum.

5.8. TPUs and GPUs, and automating AI R&D

[Yudkowsky][23:17]

I'm also wondering a little why the emphasis on "trillions". it seems to me that the terms of your Prophecy should be fulfillable by AGI tech being merely as ubiquitous as modern computers, so that many competing companies invest mere hundreds of billions in the equivalent of hardware plants. it is legitimately hard to get a chip with 50% better transistors ahead of TSMC.

[Christiano][23:17]

yes, if you are investing hundreds of billions then it is hard to pull ahead (though could still happen)

(since the upside is so much larger here, no one cares that much about getting ahead of TSMC since the payoff is tiny in the scheme of the amounts we are discussing)

[Yudkowsky][23:18]

which, like, doesn't prevent Google from tossing out TPUs that are pretty significant jumps on GPUs, and if there's a specialized application of AGI-ish tech that is especially key, you can have everything behave smoothly and still get a jump that way.

[Christiano][23:18]

I think TPUs are basically the same as GPUs

probably a bit worse

(but GPUs are sold at a 10x markup since that's the size of nvidia's lead)

[Yudkowsky][23:19]

noted; I'm not enough of an expert to directly contradict that statement about TPUs from my own knowledge.

[Christiano][23:19]

(though I think TPUs are nevertheless leased at a slightly higher price than GPUs)

[Yudkowsky][23:19]

how does Nvidia maintain that lead and 10x markup? that sounds like a pretty un-Paul-ish state of affairs given Bitcoin prices never mind AI investments.

[Christiano][23:20]

nvidia's lead isn't worth that much because historically they didn't sell many gpus

(especially for non-gaming applications)

their R&D investment is relatively large compared to the $ on the table

my guess is that their lead doesn't stick, as evidenced by e.g. Google very quickly catching up

[Yudkowsky][23:21]

parenthetically, does this mean - and I don't necessarily predict otherwise - that you predict a drop in Nvidia's stock and a drop in GPU prices in the next couple of years?

[Christiano][23:21]

nvidia's stock may do OK from riding general AI boom, but I do predict a relative fall in nvidia compared to other AI-exposed companies

(though I also predicted google to more aggressively try to compete with nvidia for the ML market and think I was just wrong about that, though I don't really know any details of the area)

I do expect the cost of compute to fall over the coming years as nvidia's markup gets eroded

to be partially offset by increases in the cost of the underlying silicon (though that's still bad news for nvidia)

[Yudkowsky][23:23]

I parenthetically note that I think the Wise Reader should be justly impressed by predictions that come true about relative stock price changes, even if Eliezer has not explicitly contradicted those predictions before they come true. there are bets you can win without my having to bet against you.

[Christiano][23:23]

you are welcome to counterpredict, but no saying in retrospect that reality proved you right if you don't 🙂

otherwise it's just me vs the market

[Yudkowsky][23:24]

I don't feel like I have a counterprediction here, but I think the Wise Reader should be impressed if you win vs. the market.

however, this does require you to name in advance a few "other AI-exposed companies".

[Christiano][23:25]

Note that I made the same bet over the last year---I make a large AI bet but mostly moved my nvidia allocation to semiconductor companies. The semiconductor part of the portfolio is up 50% while nvidia is up 70%, so I lost that one. But that just means I like the bet even more next year.

happy to use nvidia vs tsmc

[Yudkowsky][23:25]

there's a lot of noise ...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Six lessons learned from our first year - Animal Ask, published by Animal Ask on November 29, 2021 on The Effective Altruism Forum.

Wrapping up on our first operational year, we thought it would be beneficial to share an update on our work and projected impact so far. Following a stakeholder evaluation earlier in the year and completing the internal monitoring and evaluation of our pilot programme, we think there are also some key lessons that could be useful to members of the effective animal advocacy and effective altruism communities.

For anyone unfamiliar with our work, we encourage you to read our introductory post. More information on our organisation can also be found on our website. In summary, Animal Ask is a non-profit that supports existing animal advocacy organisations with research and consultancy. We help them prioritise between different legislative or corporate campaigns through in-depth, systematic research of a wide variety of potential campaigns, assessing their impact, to ensure that advocacy resources are spent on the highest priority opportunities.

We have spent our first year completing a pilot programme aimed at testing both our research process and organisational model. This pilot provided three organisations with extensive research towards their upcoming campaigns. Specifically, we supported Sinergia Animal (an international animal protection organisation working in countries in the Global South), Advocates for Animals (the UK's first law firm dedicated to animal protection law), and Sentience Politics (an anti-speciesist political think tank based in Switzerland with the goal of reducing the suffering of all sentient beings).

Alongside this, we provided assistance to multiple groups through our Ask Consultancy programme, as well as completing foundational research into different methods of evaluating animal welfare.

Animal Ask’s First Year Summary

These are top line summaries of activities from our launch in September 2020 to the present day.

Ask Prioritisation Research

144 possible interventions, or asks, were taken through our extensive research rounds across the three projects, resulting in eight extensive reports.

We have modelled the expected impact of these three collaborations by monitoring and evaluating updates in the decision making of the partner organisations, our predictions of likely counterfactuals without our involvement, and the expected value of the campaigns we recommended. Given the update in decision making we have observed, we estimate that our collaboration increased the expected value of their campaigns by ~30% - Advocates for Animals, ~50% - Sinergia Animal, and ~70% Sentience Politics.

In expectation, between the three projects this should result in ~2.3 million equivalent animal lives saved and 10s of millions affected. However, we do approach these projections with skepticism as we continue to evaluate the value of our work, and with the impact of these campaigns yet to be determined.

All three groups indicated that they are actively using our research to inform their ask decision-making. Updates on this will be released when they have finalised their strategic directions and we can more accurately report the difference in value of the campaign due to our involvement. Sentience Politics has already taken one of the interventions we suggested forward, an intervention their post-collaboration interview suggests they would not have considered independently.

We are happy to share our models with those who may be interested in further detail. We will consider requests on a case by case basis due to the sensitive nature of the data.

Ask Consultation Research

Three extensive reports for the Conservative Animal Welfare Foundation; ‘Welfare at the time of killing’, ‘Ending cages for laying hens’, and ‘Non-stun slaughter’....

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Six lessons learned from our first year - Animal Ask, published by Animal Ask on November 29, 2021 on The Effective Altruism Forum.

Wrapping up on our first operational year, we thought it would be beneficial to share an update on our work and projected impact so far. Following a stakeholder evaluation earlier in the year and completing the internal monitoring and evaluation of our pilot programme, we think there are also some key lessons that could be useful to members of the effective animal advocacy and effective altruism communities.

For anyone unfamiliar with our work, we encourage you to read our introductory post. More information on our organisation can also be found on our website. In summary, Animal Ask is a non-profit that supports existing animal advocacy organisations with research and consultancy. We help them prioritise between different legislative or corporate campaigns through in-depth, systematic research of a wide variety of potential campaigns, assessing their impact, to ensure that advocacy resources are spent on the highest priority opportunities.

We have spent our first year completing a pilot programme aimed at testing both our research process and organisational model. This pilot provided three organisations with extensive research towards their upcoming campaigns. Specifically, we supported Sinergia Animal (an international animal protection organisation working in countries in the Global South), Advocates for Animals (the UK's first law firm dedicated to animal protection law), and Sentience Politics (an anti-speciesist political think tank based in Switzerland with the goal of reducing the suffering of all sentient beings).

Alongside this, we provided assistance to multiple groups through our Ask Consultancy programme, as well as completing foundational research into different methods of evaluating animal welfare.

Animal Ask’s First Year Summary

These are top line summaries of activities from our launch in September 2020 to the present day.

Ask Prioritisation Research

144 possible interventions, or asks, were taken through our extensive research rounds across the three projects, resulting in eight extensive reports.

We have modelled the expected impact of these three collaborations by monitoring and evaluating updates in the decision making of the partner organisations, our predictions of likely counterfactuals without our involvement, and the expected value of the campaigns we recommended. Given the update in decision making we have observed, we estimate that our collaboration increased the expected value of their campaigns by ~30% - Advocates for Animals, ~50% - Sinergia Animal, and ~70% Sentience Politics.

In expectation, between the three projects this should result in ~2.3 million equivalent animal lives saved and 10s of millions affected. However, we do approach these projections with skepticism as we continue to evaluate the value of our work, and with the impact of these campaigns yet to be determined.

All three groups indicated that they are actively using our research to inform their ask decision-making. Updates on this will be released when they have finalised their strategic directions and we can more accurately report the difference in value of the campaign due to our involvement. Sentience Politics has already taken one of the interventions we suggested forward, an intervention their post-collaboration interview suggests they would not have considered independently.

We are happy to share our models with those who may be interested in further detail. We will consider requests on a case by case basis due to the sensitive nature of the data.

Ask Consultation Research

Three extensive reports for the Conservative Animal Welfare Foundation; ‘Welfare at the time of killing’, ‘Ending cages for laying hens’, and ‘Non-stun slaughter’....

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Anthropics and the Universal Distribution, published by Joe Carlsmith on November 28, 2021 on LessWrong.

(Cross-posted from Hands and Cities. Content warning: especially niche topic.)

Some readers of my recent sequence on anthropics suggested that I consider an approach that they find especially plausible — namely, UDASSA (or the “Universal Distribution” plus the “Absolute Self-Sampling Assumption”). So, partly on this prompting, and partly from pre-existing interest, I spent some time learning about UDASSA, and talking to people who like it.

What is UDASSA? Roughly, UDASSA is anthropics for people who really like the Universal Distribution (UD), which is a way of assigning prior probabilities to hypotheses (see my previous post for details). UDASSA’s hope is that, having discovered the UD, it has done a lot to solve anthropics, too: all you need to do is to apply the UD (plus some Bayesianism) to hypotheses about who you are (and in particular, which observer-moment you are).

In practice, and granted some further assumptions (what I call the “world and claw assumptions”), this means that UDASSA expects to find itself in “simpler” combination of (a) worlds, and (b) “locations” in a world (where the relevant notion of “location” is importantly up for grabs, and itself biased towards simplicity). We can think of this move as an extension of Occam’s Razor from objective worlds to centered worlds: “you know how you wanted to weight hypotheses about the world according to some notion of simplicity? Well, I want to do that with hypotheses about who I am, too.”

Is UDASSA a good approach? I think it’s important to distinguish between two claims:

The UD is cool.

The UD helps a lot with anthropics.

As I indicated in my previous post, I’m open to (1): I think the UD might well be cool, despite various issues (e.g., uncomputability, the arbitrary choice of UTM, ruling out uncomputable worlds, and so on).

But I’m more skeptical of (2). Granted the world and claw assumptions, I think the UD helps with some problems in anthropics: in particular, relative to SIA and SSA, it seems better positioned – at least in principle — to deal with infinities, and with cases that make it unclear how to count observers (some other candidate pluses, like “there are limits to my dogmatism,” seem to me less exciting).

But these benefits come with serious costs. Applying the UD to anthropics leads to unappealing combinations of: (a) extreme disconnection from normal patterns of reasoning (and/or ethical concern), and (b) cluelessness about what conclusions are actually implied.

In particular, my impression is that people tend to assume that UD-ish anthropics entails something that I call “weird SIA.” Weird SIA is supposed to act broadly like SIA, but with the addition of what I call “soul magnetism”: namely, the hypothesis that in a world where multiple people make your observations, you are more likely be some of those people than others, because some of their “locations” are “simpler.” Soul magnetism is key to the UD’s ability to handle infinities, but it’s also really epistemically (and/or ethically) unappealing in its own right. And to the extent we try to water the UD’s soul-magnetism down (it’s not clear that we can), weird SIA starts to take on more of normal SIA’s presumptuousness problem.

Beyond this, though, it’s not at all clear to me that the UD actually does imply weird SIA – or, indeed, that it implies any of the things advocates seem to hope it implies (for example, that you’re more likely to be running on a computer with thicker wires – that oh-so-clear intuitive datum). To the contrary, as far as I can tell, we’re basically clueless about what the UD says about anthropics — it all depends on which ways of extracting our observations end up coded for by the shortest programs input to ...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Anthropics and the Universal Distribution, published by Joe Carlsmith on November 28, 2021 on LessWrong.

(Cross-posted from Hands and Cities. Content warning: especially niche topic.)

Some readers of my recent sequence on anthropics suggested that I consider an approach that they find especially plausible — namely, UDASSA (or the “Universal Distribution” plus the “Absolute Self-Sampling Assumption”). So, partly on this prompting, and partly from pre-existing interest, I spent some time learning about UDASSA, and talking to people who like it.

What is UDASSA? Roughly, UDASSA is anthropics for people who really like the Universal Distribution (UD), which is a way of assigning prior probabilities to hypotheses (see my previous post for details). UDASSA’s hope is that, having discovered the UD, it has done a lot to solve anthropics, too: all you need to do is to apply the UD (plus some Bayesianism) to hypotheses about who you are (and in particular, which observer-moment you are).

In practice, and granted some further assumptions (what I call the “world and claw assumptions”), this means that UDASSA expects to find itself in “simpler” combination of (a) worlds, and (b) “locations” in a world (where the relevant notion of “location” is importantly up for grabs, and itself biased towards simplicity). We can think of this move as an extension of Occam’s Razor from objective worlds to centered worlds: “you know how you wanted to weight hypotheses about the world according to some notion of simplicity? Well, I want to do that with hypotheses about who I am, too.”

Is UDASSA a good approach? I think it’s important to distinguish between two claims:

The UD is cool.

The UD helps a lot with anthropics.

As I indicated in my previous post, I’m open to (1): I think the UD might well be cool, despite various issues (e.g., uncomputability, the arbitrary choice of UTM, ruling out uncomputable worlds, and so on).

But I’m more skeptical of (2). Granted the world and claw assumptions, I think the UD helps with some problems in anthropics: in particular, relative to SIA and SSA, it seems better positioned – at least in principle — to deal with infinities, and with cases that make it unclear how to count observers (some other candidate pluses, like “there are limits to my dogmatism,” seem to me less exciting).

But these benefits come with serious costs. Applying the UD to anthropics leads to unappealing combinations of: (a) extreme disconnection from normal patterns of reasoning (and/or ethical concern), and (b) cluelessness about what conclusions are actually implied.

In particular, my impression is that people tend to assume that UD-ish anthropics entails something that I call “weird SIA.” Weird SIA is supposed to act broadly like SIA, but with the addition of what I call “soul magnetism”: namely, the hypothesis that in a world where multiple people make your observations, you are more likely be some of those people than others, because some of their “locations” are “simpler.” Soul magnetism is key to the UD’s ability to handle infinities, but it’s also really epistemically (and/or ethically) unappealing in its own right. And to the extent we try to water the UD’s soul-magnetism down (it’s not clear that we can), weird SIA starts to take on more of normal SIA’s presumptuousness problem.

Beyond this, though, it’s not at all clear to me that the UD actually does imply weird SIA – or, indeed, that it implies any of the things advocates seem to hope it implies (for example, that you’re more likely to be running on a computer with thicker wires – that oh-so-clear intuitive datum). To the contrary, as far as I can tell, we’re basically clueless about what the UD says about anthropics — it all depends on which ways of extracting our observations end up coded for by the shortest programs input to ...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Redwood Research is hiring for several roles, published by Jack R on November 29, 2021 on LessWrong.

Redwood Research does applied AI alignment research. We’re led by Nate Thomas (CEO), Buck Shlegeris (CTO), and Bill Zito (COO), and our board is Holden Karnofsky, Paul Christiano, and Nate Thomas. To learn more about our current project, you can read a project update from September or Paul’s “Why I’m excited about Redwood Research’s current project.”

In addition to our primary work of applied AI alignment research, Redwood hosts and operates Constellation, a shared office space we created to foster knowledge-sharing and collaboration between longtermist organizations. People from the following organizations often work from the space: Alignment Research Center, MIRI, and Open Philanthropy.

We’re hiring for several roles, listed below in order of which roles we’re excited to get more applications for right now (subject to change within a month):

Redwood / Constellation Generalist

Research and Engineering Staff

Constellation Operations Manager

Constellation Member Experience Manager

Constellation Sous Chef

If you have any questions, feel free to email Bill ([email protected]) about generalist/ops roles or Buck ([email protected]) about technical roles.

Below is a picture taken from the office -- we have beautiful views in all directions!

Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Redwood Research is hiring for several roles, published by Jack R on November 29, 2021 on LessWrong.

Redwood Research does applied AI alignment research. We’re led by Nate Thomas (CEO), Buck Shlegeris (CTO), and Bill Zito (COO), and our board is Holden Karnofsky, Paul Christiano, and Nate Thomas. To learn more about our current project, you can read a project update from September or Paul’s “Why I’m excited about Redwood Research’s current project.”

In addition to our primary work of applied AI alignment research, Redwood hosts and operates Constellation, a shared office space we created to foster knowledge-sharing and collaboration between longtermist organizations. People from the following organizations often work from the space: Alignment Research Center, MIRI, and Open Philanthropy.

We’re hiring for several roles, listed below in order of which roles we’re excited to get more applications for right now (subject to change within a month):

Redwood / Constellation Generalist

Research and Engineering Staff

Constellation Operations Manager

Constellation Member Experience Manager

Constellation Sous Chef

If you have any questions, feel free to email Bill ([email protected]) about generalist/ops roles or Buck ([email protected]) about technical roles.

Below is a picture taken from the office -- we have beautiful views in all directions!

Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Redwood Research is hiring for several roles, published by Jack R on November 29, 2021 on The Effective Altruism Forum.

Redwood Research does applied AI alignment research. We’re led by Nate Thomas (CEO), Buck Shlegeris (CTO), and Bill Zito (COO), and our board is Holden Karnofsky, Paul Christiano, and Nate Thomas. To learn more about our current project, you can read a project update from September or Paul’s “Why I’m excited about Redwood Research’s current project.”

In addition to our primary work of applied AI alignment research, Redwood hosts and operates Constellation, a shared office space we created to foster knowledge-sharing and collaboration between longtermist organizations. People from the following organizations often work from the space: Alignment Research Center, MIRI, and Open Philanthropy.

We’re hiring for several roles, listed below in order of which roles we’re excited to get more applications for right now (subject to change within a month):

Redwood / Constellation Generalist

Research and Engineering Staff

Constellation Operations Manager

Constellation Member Experience Manager

Constellation Sous Chef

If you have any questions, feel free to email Bill ([email protected]) about generalist/ops roles or Buck ([email protected]) about technical roles.

Below is a picture taken from the office -- we have beautiful views in all directions!

(Note: Even though I use "we" throughout this post, I don't work for Redwood -- I am on a work trial, though.)

Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Redwood Research is hiring for several roles, published by Jack R on November 29, 2021 on The Effective Altruism Forum.

Redwood Research does applied AI alignment research. We’re led by Nate Thomas (CEO), Buck Shlegeris (CTO), and Bill Zito (COO), and our board is Holden Karnofsky, Paul Christiano, and Nate Thomas. To learn more about our current project, you can read a project update from September or Paul’s “Why I’m excited about Redwood Research’s current project.”

In addition to our primary work of applied AI alignment research, Redwood hosts and operates Constellation, a shared office space we created to foster knowledge-sharing and collaboration between longtermist organizations. People from the following organizations often work from the space: Alignment Research Center, MIRI, and Open Philanthropy.

We’re hiring for several roles, listed below in order of which roles we’re excited to get more applications for right now (subject to change within a month):

Redwood / Constellation Generalist

Research and Engineering Staff

Constellation Operations Manager

Constellation Member Experience Manager

Constellation Sous Chef

If you have any questions, feel free to email Bill ([email protected]) about generalist/ops roles or Buck ([email protected]) about technical roles.

Below is a picture taken from the office -- we have beautiful views in all directions!

(Note: Even though I use "we" throughout this post, I don't work for Redwood -- I am on a work trial, though.)

Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.