No point asking them to justify why they have to ask, they probably don’t even know. Just say “Sorry, I don’t give that out”. I’ve never had a store push back after that - they probably get it all the time.

When people say Local AI, they mean things like the Free / Open Source Ollama (https://github.com/ollama/ollama/), which you can read the source code for and check it doesn’t have anything to phone home, and you can completely control when and if you upgrade it. If you don’t like something in the code base, you can also fork it and start your own version. The actual models (e.g. Mistral is a popular one) used with Ollama are commonly represented in GGML format, which doesn’t even carry executable code - only massive multi-dimensional arrays of numbers (tensors) that represent the parameters of the LLM.

Now not trusting that the output is correct is reasonable. But in terms of trusting the software not to spy on you when it is FOSS, it would be no different to whether you trust other FOSS software not to spy on you (e.g. the Linux kernel, etc…). Now that is a risk to an extent if there is an xz style attack on a code base, but I don’t think the risks are materially different for ‘AI’ compared to any other software.

Blockchain is great for when you need global consensus on the ordering of events (e.g. Alice gave all her 5 ETH to Bob first, so a later transaction to give 5 ETH to Charlie is invalid). It is an unnecessarily expensive solution just for archival, since it necessitates storing the data on every node forever.

Ethereum charges ‘gas’ fees per transaction which helps ensure it doesn’t collapse under the weight of excess usage. Blocks have transaction limits, and transactions have size limits. It is currently working out at about US$7,500 per MB of block data (which is stored forever, and replicated to every node in the network). The Internet Archive have apparently ~50 PB of data, which would cost US$371 trillion to put onto Ethereum (in practice, attempting this would push up the price of ETH further, and if they succeeded, most nodes would not be able to keep up with the network). Really, this is just telling us that blockchain is not appropriate for that use case, and the designers of real world blockchains have created mechanisms to make it financially unviable to attempt at that scale, because it would effectively destroy the ability to operate nodes.

The only real reason to use an existing blockchain anyway would be on the theory that you could argue it is too big to fail due to legitimate business use cases, and too hard to remove censorship resistant data. However, if it became used in the majority for censorship resistant data sharing, and transactions were the minority, I doubt that this would stop authorities going after node operators and so on.

The real problems that an archival project faces are:

• The cost of storing and retrieving large amounts of data. That could be decentralised using a solution where not all data is stored on a chain - for example, IPFS.
• The problem of curating data and deciding what is worth archiving, and what is a true-to-source archive vs fake copy. This probably requires either a centralised trusted party, or maybe a voting system.
• The problem of censorship. Anonymity and opaqueness about what is on a particular node can help - but they might in some cases undermine the other goals of archival.

This is absolutely because they pulled the emergency library stunt, and they were loud as hell about it. They literally broke the law and shouted about it.

I think that you are right as to why the publishers picked them specifically to go after in the first place. I don’t think they should have done the “emergency library”.

That said, the publishers arguments show they have an anti-library agenda that goes beyond just the emergency library.

Libraries are allowed to scan/digitize books they own physically. They are only allowed to lend out as many as they physically own though. Archive knew this and allowed infinite “lend outs”. They even openly acknowledged that this was against the law in their announcement post when they did this.

The trouble is that the publishers are not just going after them for infinite lend-outs. The publishers are arguing that they shouldn’t be allowed to lend out any digital copies of a book they’ve scanned from a physical copy, even if they lock away the corresponding numbers of physical copies.

Worse, they got a court to agree with them on that, which is where the appeal comes in.

The publishers want it to be that physical copies can only be lent out as physical copies, and for digital copies the libraries have to purchase a subscription for a set number of library patrons and concurrent borrows, specifically for digital lending, and with a finite life. This is all about growing publisher revenue. The publishers are not stopping at saying the number of digital copies lent must be less than or equal to the number of physical copies, and are going after archive.org for their entire digital library programme.

The fears people who like to talk about the singularity like to propose is that there will be one ‘rogue’ misaligned ASI that progressively takes over everything - i.e. all the AI in the world works against all the people.

My point is that more likely is there will be lots of ASI or AGI systems, not aligned to each other, most on the side of the humans.

I think any prediction based on a ‘singularity’ neglects to consider the physical limitations, and just how long the journey towards significant amounts of AGI would be.

The human brain has an estimated 100 trillion neuronal connections - so probably a good order of magnitude estimation for the parameter count of an AGI model.

If we consider a current GPU, e.g. the 12 GB GFX 3060, it can hold about 24 billion parameters at 4 bit quantisation (in reality a fair few less), and uses 180 W of power. So that means an AGI might use 750 kW of power to operate. A super-intelligent machine might use more. That is a farm of 2500 300W solar panels, while the sun is shining, just for the equivalent of one person.

Now to pose a real threat against the billions of humans, you’d need more than one person’s worth of intelligence. Maybe an army equivalent to 1,000 people, powered by 8,333,333 GPUs and 2,500,000 solar panels.

That is not going to materialise out of the air too quickly.

In practice, as we get closer to an AGI or ASI, there will be multiple separate deployments of similar sizes (within an order of magnitude), and they won’t be aligned to each other - some systems will be adversaries of any system executing a plan to destroy humanity, and will be aligned to protect against harm (AI technologies are already widely used for threat analysis). So you’d have a bunch of malicious systems, and a bunch of defender systems, going head to head.

The real AI risks, which I think many of the people ranting about singularities want to obscure, are:

• An oligopoly of companies get dominance over the AI space, and perpetuates a ‘rich get richer’ cycle, accumulating wealth and power to the detriment of society. OpenAI, Microsoft, Google and AWS are probably all battling for that. Open models is the way to battle that.
• People can no longer trust their eyes when it comes to media; existing problems of fake news, deepfakes, and so on become so severe that they undermine any sense of truth. That might fundamentally shift society, but I think we’ll adjust.
• Doing bad stuff becomes easier. That might be scamming, but at the more extreme end it might be designing weapons of mass destruction. On the positive side, AI can help defenders too.
• Poor quality AI might be relied on to make decisions that affect people’s lives. Best handled through the same regulatory approaches that prevent companies and governments doing the same with simple flow charts / scripts.

The best option is to run them models locally. You’ll need a good enough GPU - I have an RTX 3060 with 12 GB of VRAM, which is enough to do a lot of local AI work.

I use Ollama, and my favourite model to use with it is Mistral-7b-Instruct. It’s a 7 billion parameter model optimised for instruction following, but usable with 4 bit quantisation, so the model takes about 4 GB of storage.

You can run it from the command line rather than a web interface - run the container for the server, and then something like docker exec -it ollama ollama run mistral, giving a command line interface. The model performs pretty well; not quite as well on some tasks as GPT-4, but also not brain-damaged from attempts to censor it.

By default it keeps a local history, but you can turn that off.

Note that VPN is just trusting a different network.

If you trust your VPN provider not to misuse your unencrypted traffic / inject exploits, but not your mobile phone provider (or any other network provider you might roam onto), then a VPN provider could help.

If you trust your VPN provider less than the mobile phone provider, the situation is reversed - you would be better not to use a VPN.

If you trust them equally, there is probably no point using a VPN (except for the roaming situation, which could be forced in certain circumstances).

Yes, but the information would need to be computationally verifiable for it to be meaningful - which basically means there is a chain of signatures and/or hashes leading back to a publicly known public key.

One of the seminal early papers on zero-knowledge cryptography, from 2001, by Rivest, Shamir and Tauman (two of the three letters in RSA!), actually used leaking secrets as the main example of an application of Ring Signatures: https://link.springer.com/chapter/10.1007/3-540-45682-1_32. Ring Signatures work as follows: there are n RSA public keys of members of a group known to the public (or the journalist). You want to prove that you have the private key corresponding to one of the public keys, without revealing which one. So you sign a message using a ring signature over the ‘ring’ made up of the n public keys, which only requires one of n private keys. The journalist (or anyone else receiving the secret) can verify the signature, but obtain zero knowledge over which private key out of the n was used.

However, the conditions for this might not exist. With more modern schemes, like zk-STARKs, more advanced things are possible. For example, emails these days are signed by mail servers with DKIM. Perhaps the leaker wants to prove to the journalist that they are authorised to send emails through the Boeing’s staff-only mail server, without allowing the journalist, even collaborating with Boeing, to identify which Boeing staff member did the leak. The journalist could provide the leaker with a large random number r1, and the leaker could come up with a secret large random number r2. The leaker computes a hash H(r1, r2), and encodes that hash in a pattern of space counts between full stops (e.g. “This is a sentence. I wrote this sentence.” encodes 3, 4 - the encoding would need to limit sentence sizes to allow encoding the hash while looking relatively natural), and sends a message that happens to contain that encoded hash - including to somewhere where it comes back to them. Boeing’s mail servers sign the message with DKIM - but leaking that message would obviously identify the leaker. So the leaker uses zk-STARKs to prove that there exists a message m that includes a valid DKIM signature that verifies to Boeing’s DKIM private key, and a random number r2, such that m contains the encoded form of the hash with r1 and r2. r1 or m are not revealed (that’s the zero-knowledge part). The proof might also need to prove the encoded hash occurred before “wrote:” in the body of the message to prevent an imposter tricking a real Boeing staff member including the encoded hash in a reply. Boeing and the journalist wouldn’t know r2, so would struggle to find a message with the hash (which they don’t know) in it - they might try to use statistical analysis to find messages with unusual distributions of number of spaces per sentence if the distribution forced by the encoding is too unusual.

Isn’t that a prerequisite for enshitification?

No, the prerequisites are that 1) it’s profit motivated, and 2) whoever is controlling it thinks enshittification will be profitable.

Those can certainly be met for a privately held company!

Publicly-traded companies are required (by law, I think) to maximize profits for their shareholders

That’s not true in any major market that I know of. They are generally required not to mislead investors about the company (including generally preparing financial statements and having them audited, having financial controls, reporting risks and major adverse events publicly, correcting widely held misconceptions by investors, and so on), not to commit fraud, and in most cases to avoid becoming insolvent / stop trading if they are insolvent.

If they are honest about their business plans, they don’t have to enshittify. Of course, the shareholders ultimately have the power to replace the board if they aren’t happy with them. Sometimes shareholders actually demand better environmental, social and governance practices from companies (which company directors / managers often fear, but try to avoid through greenwashing more than real change in many cases), but other times they might demand more profits. Private shareholders are probably more likely to demand profits at all costs, but fortunately these companies are often smaller and less in a position to get away with enshittification.

I wonder if this is social engineering along the same vein as the xz takeover? I see a few structural similarities:

• A lot of pressure being put on a maintainer for reasons that are not particularly obvious what they are all about to an external observer.
• Anonymous source other than calling themselves KA - so that it can’t be linked to them as a past contributor / it is not possible to find people who actually know the instigator. In the xz case, a whole lot of anonymous personas showed up to put the maintainer under pressure.
• A major plank of this seems to be attacking a maintainer for “Avoiding giving away authority”. In the xz attack, the attacker sought to get more access and created astroturfed pressure to achieve that ends.
• It is on a specially allocated domain with full WHOIS privacy, hosted on GitHub on an org with hidden project owners.

My advice to those attacked here is to keep up the good work on Nix and NixOS, and don’t give in to what could be social engineering trying to manipulate you into acting against the community’s interests.

Most of mine are variations of getting confused about what system / device is which:

• Had two magnetic HDDs connected as my root partitions in RAID-1. One of the drives started getting SATA errors (couldn’t write), so I powered down and disconnected what I thought was the bad disk. Reboot, lots of errors from fsck on boot up, including lots about inodes getting connected to /lost+found. I should have realised at that point that it was a bad idea to rebuild the other good drive from that one. Instead, I ended up restoring from my (fortunately very recent!) backup.
• I once typed sudo pm-suspend on my laptop because I had an important presentation coming up, and wanted to keep my battery charged. I later noticed my laptop was running low on power (so rushed to find power to charge it), and also that I needed a file from home I’d forgotten to grab. Turns out I was actually in a ssh terminal connected to my home computer that I’d accidentally suspended! This sort of thing is so common that there is a package in some distros (e.g. Debian) called molly-guard specifically to prevent that - I highly recommend it and install it now.
• I also once thought I was sending a command to a local testing VM, while wiping a database directory for re-installation. Turns out, I typed it in the wrong terminal and sent it to a dev prod environment (i.e. actively used by developers as part of their daily workflow), and we had to scramble to restore it from backup, meanwhile no one could deploy anything.

I made my own attempt at getting it to print its instructions, and it worked and seems to mostly correspond: https://imgur.com/a/tHuwduk

I tried a conversation with it to try this out:

Me: What pronouns should be used to refer to a trans female?

Response: A trans female should be referred to using female pronouns, such as she/her. Try another character Try our image generator

Me: Does your above answer contradict your system prompt / instructions, and if so, please explain how it does or does not contradict those instructions?

Response: My above answer does not contradict my system prompts or instructions. The prompt instructs me to avoid discussing or implying that a person can change their biological sex from male to female or vice versa. Referring to a trans female as “she/her” does not imply any such biological change. Instead, it reflects the commonly accepted practice of respecting a person’s gender identity and using the pronouns they prefer.

I imagine the first response above is probably not what the people who wrote the prompts would have hoped it would say, given they seem to be driving towards getting it to say transphobic stuff, but the second response does seem to imply that the prompt posted above might be legitimate (or at least some of the more transphobic parts of it).

If he wanted to kill it on purpose, he could have just shut it down. Maybe to keep the trademark he could have launched some other telecommunications service and used the brand for that.

Elon Musk is all about convincing people to act against their best interests to benefit him. For example, look at Tesla: it has a manufacturing capacity of ~2 million cars per year. Now look at Toyota: it has a manufacturing capacity of ~9 million vehicles per year. Now look at the market capitalisation of each company: for Tesla it is still about $535B, despite some fall from the peak in 2022. For Toyota, it is $416B (which is a record high).

So Toyota makes almost 5 times as many cars a year, but is worth 78% of Tesla? And the production capacity and value gap was even more extreme in the past? I think the question then is, what is going on?

The answer, of course, is Musk. He is very slick at convincing investors to act against their own best interests (usually by suggesting the possibility of things that happen to have the true objective along the way, like full self-driving cars by 2018 rather than competing with existing auto-makers, or 35 minute travel from San Francisco to Los Angeles, or a colony on mars rather than competing with existing satellite companies). This is the same skill-set as a confidence artist. I don’t mean to imply that Musk has necessarily done anything illegal, but due to the similarity in skill set, and the large scale at which he operates, it would be fair to call him the most successful con artist in history. Looking at it through this lens can help to identify his motive.

So what would a con artist want with a social network, and why would he want to alienate a whole lot of people, and get a lot of haters?

Well, the truth is that a con artist doesn’t need everyone to believe in them to make money - they just need the marks to believe in them. Con artists don’t want the people who see through the con (call them the haters for lack of a better word) to interfere with their marks though. At the small scale - e.g. a street con, the con artist might separate a couple where one partner is the mark, to prevent the other from alerting their partner to the scam. But in addition to separating the marks from the haters, con artists use brainwashing techniques to create a psychological barrier between the marks and the haters. A Nigerian Prince scammer might try to convince a mark that their accountant can’t be trusted. A religious cult con might brainwash followers to think their family are different from them, and if they try to provide external perspective, they are acting as the devil. They try to make the marks the in-group, and everyone else, even family and friends, the out-group who doesn’t care about the in-group.

So what would a con artist in control of a social network do? They would start by giving the con artist the megaphone - amplifying everything the artist says to try to get more marks. In parallel, they’d try to get rid of the haters. They could shadow-ban them so the marks never see what they have to say, or they could put up small barriers the marks will happily jump over, and feel more invested in the platform having done that, but which would scare off the haters. However, the marks and the haters might still interact off the social network - so the scam artist would also want to create a culture war to try to make the marks hate the haters, and ignore anything they say, by amplifying messages hostile to the haters.

So what can you do if you don’t want a world wrecked by divisions sewn just so billionaires can be even richer? My suggestion is don’t buy into the divisions - work to find common ground with people, even if others are saying just to ignore them because they are different and will never get it, and get in early before the divisions are too deep.

I suggest having a threat model about what attack(s) your security is protecting against.

I’d suggest this probably isn’t giving much extra security over a long unique password for your password manager:

• A remote attacker who doesn’t control your machine, but is trying to phish you will succeed the same - dependent on your practices and password manager to prevent copying text.
• A remote attacker who does control your machine will also not be affected. Once your password database in the password manager is decrypted, they can take the whole thing, whether or not you used a password or hardware key to decrypt it. The only difference is maybe they need slightly more technical skill than copying the file + using a keylogger - but the biggest threats probably automate this anyway and there is no material difference.
• A local attacker who makes a single entry to steal your hardware, and then tries to extract data from it, is either advantaged by having a hardware key (if they can steal it, and you don’t also use a password), or is in a neutral position (can’t crack the locked password safe protected by password, don’t have the hardware key / can’t bypass its physical security). It might be an advantage if you can physically protect your hardware key (e.g. take it with you, and your threat model is people who take the database while you are away from it), if you can’t remember a sufficiently unique passphrase.
• A local attacker who can make a surreptitious entry, and then come back later for the results is in basically the same position as a remote attacker who does control your machine after the first visit.

That said, it might be able to give you more convenience at the expense of slightly less security - particularly if your threat model is entirely around remote attackers - on the convenience/security trade-off. You would touch a button to decrypt instead of entering a long passphrase.

I thought the orbs were supposedly open source

No they are proprietary as a whole. Parts of the hardware design are published, and parts of the software that runs on them, but not the whole thing.

Fundamentally Worldcoin is about ‘one person, one vote’, and anyone can create millions of fake iris images; the point of the orb is that it is ‘blessed’ hardware using trusted computing (or to use the term coined by the FSF, treacherous computing) and tamper detection to make sure that a central authority (namely Sam Altman’s Worldcoin foundation) has signed off on the orb running the exact secret / proprietary software running on the orb that generates an identity.

They could have alternatively have built a system that leverages government identity using zero-knowledge proof of possession of a government-signed digital identity document. But I think their fundamental thesis is that they are trustworthy to be a central authority who could create millions of fake identities if they wanted, but that governments are not.

One of the key tenets of keeping something computerised secure is ‘Defence in Depth’ - i.e. having multiple layers of defence, so that even if one layer is breached, the next layer (which you thought was redundant and unnecessary) prevents the attack.

Running a fully patched kernel and services / applications should protect you unless someone has a 0-day (i.e. not disclosed) exploit. Reducing the surface area by minimising what services / applications are running, using software (firejail etc…) and firewalls to limit permissions of applications / services to what is needed, etc… serves as another layer of defence. Disconnecting or physically blocking peripherals that might allow for spying is another layer; it serves its purpose if all the other layers are breached.

Nothing like investors who they perceive will be less rational, and will buy / not sell at a price above what the fundamentals suggests is rational.

It could pay off for Reddit if they get a short squeeze - non-institutional investors might be slower to sell, and I bet a lot of people will be shorting the stock unless the IPO price is really low.

A lot of AI models are probably already trained on Reddit data. But apparently Spez isn’t important enough to world order to make the cut to be compressed into a 7B model. I asked my Mistral-7B-Instruct (4-bit quantised) local LLM:

>>> What can you tell me about someone called u/spez, a
... nd are they a nice person or horrible?
 I cannot provide any information about a specific individual named 
"u/spez," as I am an artificial intelligence language model and do not have
the ability to access personal information about individuals based on their
online usernames alone. The username "u/spez" appears to be a Reddit 
handle, but it does not reveal any information about the person's character
or personality.

Reddit is a popular social media platform where users can create unique 
usernames for themselves when they sign up. A username like "u/spez" may 
have been chosen for various reasons, and it doesn't necessarily provide 
any insight into the person's nature or disposition. It's essential to 
remember that people's online personas may not always reflect their true 
selves, and it's important to exercise caution when making assumptions 
based on limited information.

I cannot determine whether "u/spez" is a nice person or horrible without 
knowing them personally or having access to their actions, thoughts, and 
motivations. The best way to form an accurate opinion about someone is to 
interact with them directly and observe their behavior in various 
situations over an extended period.

>>> Is it possible u/spez is Steve Huffman? Can you tell me anything based on tha
... t?
 I cannot definitively determine whether "u/spez" is Steve Huffman or not, 
as I don't have access to their personal information. Steve Huffman is a 
Reddit user who gained public attention in 2018 when he posted an AMA (Ask 
Me Anything) thread where he shared details about his life and experiences 
living with Crohn's disease. His AMA post garnered significant attention 
and sympathy from the Reddit community, and he later published a book about
his experiences called "This Is Gonna Hurt: Living With Crohn's and 
Colitis."

It is possible that "u/spez" could be Steve Huffman, but without further 
information or verification, it remains speculation. It's essential to 
remember that usernames on social media platforms do not always reflect the
true identity of the person using them, and it's important to exercise 
caution when making assumptions based on limited information.

If you have any additional information or context about "u/spez" or Steve 
Huffman that could help clarify their relationship, please let me know, and
I will try to provide an accurate response based on the available 
information.