Today marks two years since I first set up an e-ink dis­play in my mom’s apart­ment to help her live on her own with am­ne­sia. The dis­play has worked ex­tremely well dur­ing those two years, so I’m shar­ing the ba­sic set-up in case oth­ers find it use­ful for sim­i­lar sit­u­a­tions.

Note: un­less you have spe­cific ex­pe­ri­ence car­ing for some­one who has am­ne­sia but not de­men­tia, please do not of­fer care sug­ges­tions.

In June 2022 the side-ef­fects of a long surgery left my mom with per­ma­nent an­tero­grade am­ne­sia: she can no longer form new long-term mem­o­ries. Memory is­n’t just one neu­ro­log­i­cal sys­tem, so very oc­ca­sion­ally she will be able to re­mem­ber cer­tain types of things. But for the most part, if she hears or sees some­thing, a few min­utes later she will no longer re­mem­ber it.

To med­ical pro­fes­sion­als her con­di­tion looks a lot like de­men­tia — am­ne­sia is a com­mon symp­tom of de­men­tia — but she does­n’t have de­men­tia. One dif­fer­ence is that (as I un­der­stand it) de­men­tia is a pro­gres­sive dis­ease, while this am­ne­sia is sta­ble. There is no cure.

Someday I might post about the ex­pe­ri­ence about car­ing for her, but for now I’ll just say that this type of am­ne­sia is not some­thing one should wish on one’s worst en­e­mies.

My mom still lives on her own in an apart­ment. Because she can­not re­mem­ber things, she goes through each day in a state of low-grade anx­i­ety about where her grown chil­dren are and whether they are all right. She feels she has­n’t heard from any of us in a long time. This anx­i­ety man­i­fests as ex­tremely fre­quent at­tempts to call or text us.

Paper notes and other forms of re­minders did­n’t seem to help, and would be­come out of date even if they weren’t mis­placed. My sib­lings and I would call to let her know we were okay, but five min­utes later she’d be back to be­ing wor­ried. She was­n’t in the habit of scrolling back through text mes­sages, so once she’d read a mes­sage, it was im­me­di­ately for­got­ten and ef­fec­tively lost.

I thought some sort of un­ob­tru­sive, al­ways-on de­vice in­stalled in her apart­ment might be able to show her notes writ­ten by my sib­lings and me.

My goal was to find a dis­play that:

Could stay on for months on end

Would let my sib­lings and I eas­ily post short mes­sages to it that would re­main vis­i­ble un­til re­placed

Was large enough and easy enough to read with­out glasses

Required no in­ter­ac­tion to wake or read and was rel­a­tively fool­proof (touching it would­n’t dis­rupt it)

Would boot di­rectly into dis­play­ing mes­sages (no in­ter­ac­tion needed to start an app)

Was not en­shit­ti­fied with a sub­scrip­tion ser­vice or pro­pri­etary app store

Would not look out of place in a home

Given the above de­sign goals, I searched for a tablet-size elec­tronic ink dis­play with Wi-Fi con­nec­tiv­ity and a de­cent web browser.

One de­vice that seemed to fit my pa­ra­me­ters was the BOOX Note Air2 Series. At the time it cost US$500, which is ex­pen­sive but is still far cheaper than screens in­tended for use as com­mer­cial re­tail dis­plays. It’s mar­keted as a note-tak­ing de­vice and ebook reader, but it also has a ca­pa­ble web browser. It’s big enough to read from a few feet away.

A crit­i­cal ques­tion I could­n’t an­swer on­line was whether I’d be able to have the de­vice au­to­mat­i­cally start its web browser and have that browser dis­play a des­ig­nated start page. Happily, when the de­vice ar­rived I was able to con­firm it could do both of those things.

The phys­i­cal case of the Note Air2 looks rea­son­ably nice and not par­tic­u­larly tech-y. The e-ink dis­play is clear and leg­i­ble; it re­freshes quickly enough to not be dis­tract­ing. By de­fault the de­vice’s back­light was turned on but I could turn it off.

I found a small metal stand to serve an easel for the dis­play so that it felt more like a pic­ture frame.

Since the phys­i­cal de­vice was sat­is­fac­tory, the next step was writ­ing a sim­ple web­site that could drive the dis­play. The site would have two pages:

A Board page show­ing the mes­sages. The e-ink de­vice would boot into show­ing this page. This is the only page my mom needed to see.

A Compose page my sib­lings and I write mes­sages and save them to be dis­played.

The de­vice needed to run for months, and needed to be re­silient in the case of net­work and ser­vice fail­ures. At the same time, I also needed to be able to re­motely up­date not only the mes­sages be­ing dis­played, but the soft­ware dis­play­ing those mes­sages.

With that in mind, I fac­tored the Board page into an outer frame and an in­ner page:

The top-level outer frame acts as a thin shell around the in­ner page. At top of every hour, the outer frame re­loads the in­ner page to pick up po­ten­tial soft­ware changes. If the net­work is down and the in­ner page does­n’t re­load, the frame just tries again an hour later. To max­i­mize re­li­a­bil­ity, the outer frame has very lit­tle logic and no ex­ter­nal de­pen­den­cies.

The in­ner page ac­tu­ally dis­plays the mes­sages. Every 5 min­utes it queries a sim­ple web ser­vice for mes­sage data and dis­plays the mes­sages. The in­ner page con­tains a small amount of logic, but as few de­pen­den­cies as pos­si­ble.

Since it’s es­sen­tially im­pos­si­ble to de­bug any­thing that hap­pens on the de­vice, I made as much use of vanilla HTML and CSS as pos­si­ble. I used a small amount of JavaScript but no frame­work or other li­braries.

The Compose page pre­sents a sim­ple web form my sib­lings and I can use to com­pose and save a mes­sage. I de­signed the form to work well on a phone screen so that we can write mes­sages when we’re out and about. A small web app man­i­fest lets us save the Compose page to a phone’s home screen as an icon for quick ac­cess.

The whole site is tiny, en­tails no build process, and with the ex­cep­tion of the ser­vice (below) is just sta­tic files.

I was con­cerned about the pos­si­bil­ity of e-ink burn-in, so the Board page ran­domly changes which mes­sage ap­pears where. Other vi­sual el­e­ments like the date and time al­ter­nate from side to side, with the in­ten­tion that no sin­gle pixel is al­ways on.

To style the note text I chose the free Architect’s Daughter font for a hand­writ­ten feel. This font works well on the e-ink dis­play. Labels are dis­played in Open Sans.

One small chal­lenge was max­i­miz­ing the size of the mes­sage text. Sometimes a mes­sage is just a word or two; other times it might be sev­eral sen­tences. A sin­gle font size can’t ac­com­mo­date such a wide range of text con­tent. I could­n’t find a pure CSS way to au­to­mat­i­cally max­i­mize font size so that a text el­e­ment with word wrap­ping would dis­play with­out clip­ping.

I ended up writ­ing a small JavaScript func­tion to max­i­mize font size: it makes the text in­vis­i­ble (via CSS vis­i­bil­ity: hid­den), tries dis­play­ing the text at a very large size, and then tries suc­ces­sively smaller font sizes un­til it finds a size that lets all the text fit. It then makes the text vis­i­ble again.

Just a tiny amount of text data is nec­es­sary to drive the dis­play, so I was happy to find the min­i­mal­ist JsonStorage ser­vice that was per­fect for this pro­ject. A sin­gle JSON ob­ject stores the text and meta­data for the cur­rent set of mes­sages. The Compose page can save to the ser­vice with a POST re­quest, and the Board page can re­trieve the data with a GET.

The ser­vice has a free tier that I started with, but I liked the ser­vice so much that I even­tu­ally paid for a $1/month ba­sic tier. (It ap­pears that tier is now $5/month.)

I spent a cou­ple of weeks work­ing on the soft­ware and let­ting it run for long pe­ri­ods of time. I was pleas­antly sur­prised that the Boox dis­play worked as well as it did and seemed to stay up in­def­i­nitely.

I brought the dis­play over to my mom’s apart­ment on November 12, 2022, turned it on, joined it to her Wi-Fi, and re­booted it to con­firm every­thing worked in the new en­vi­ron­ment.

I thought the bath­room counter might be a good place for it, but my mom thought she’d rather have it in her bed­room, so we found a home for it on a win­dowsill.

My mom was happy with the dis­play right away.

Despite her am­ne­sia, my mom came to re­mem­ber that this dis­play ex­ists and what it’s for. She looks for­ward to see­ing up­dates from her chil­dren on it.

If we tell her about some­thing that’s com­ing up, she of­ten asks whether we’ve al­ready put that event on the MomBoard. On the flip side, we have to be care­ful to keep it up to date; if we fail to take down a mes­sage that no longer ap­plies, it con­fuses her.

Looking back, the dis­play is es­sen­tially the only in­ter­ven­tion of any kind we’ve tried that’s ac­tu­ally been suc­cess­ful at im­prov­ing her qual­ity of life (and ours). One rea­son it’s worked so well is that it did­n’t re­quire her to learn any­thing new. Without the abil­ity to re­mem­ber new things, it’s vir­tu­ally im­pos­si­ble for her to learn a new skill or to form new habits.

The de­vice’s re­li­a­bil­ity has sur­passed my ex­pec­ta­tions. There was one pe­riod where the de­vice seemed to stop work­ing, but I traced the prob­lem to a faulty Wi-Fi hub; af­ter that was re­placed, it’s worked flaw­lessly since. For my part, keep­ing the soft­ware as sim­ple as pos­si­ble and stick­ing to vanilla web tech­nolo­gies surely helped avoid bugs.

The dis­play still looks great, and it still dis­plays mes­sages day in and day out.

If you want to try to set up some­thing sim­i­lar to what I de­scribe here, I’m happy to an­swer tech­ni­cal ques­tions or share ad­vice.

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This is the hard­ware be­fore it went into the ma­chines.

This is the hard­ware be­fore it went into the ma­chines.

We are Kenton Varda and Jade Wang. We’ve been mar­ried since 2014. This is our house, where we live with our two kids, in Austin, Texas.

* Started and is tech lead of the Cloudflare Workers server­less com­pute plat­form.

Jade is an en­tre­pre­neur. She:

* Holds a PhD in neu­ro­science and did re­search at NASA

* Was Head of Startups at Cloudflare

* Advises and in­vests in star­tups, par­tic­u­larly in Austin

The lead ar­chi­tect was Richard Varda, Kenton’s fa­ther. Rich is an ac­com­plished ar­chi­tect who has de­signed every­thing from houses to sky­scrap­ers. Among other things, he de­signed The Kingdom Centre in Riyadh, Saudi Arabia, and The Musical Instrument Museum in Phoenix, Arizona. Rich was also VP of Architecture at Target for many years.

Many fea­tures of the house were de­signed di­rectly by Kenton and Jade. For ex­am­ple, Kenton de­signed the game sta­tion cab­i­netry, of­fice con­fer­ence table, cat shelves, con­duit rout­ing, and most tech­ni­cal fea­tures of the house.

Additionally, we worked with Thom Lasley and oth­ers at RSP Architects. RSP nor­mally does com­mer­cial build­ings, not houses, but Rich was work­ing with RSP on other pro­jects at the time and had known Thom for decades, so it made sense.

Blue Horse Building & Design was our gen­eral con­trac­tor who built the house.

The house was com­pleted in late 2023. We orig­i­nally bought the prop­erty in 2019, and be­gan con­struc­tion in mid-2021. Yeah, it took a while.

This site was de­signed and coded by Kenton with pho­tos taken by Kenton, Jade, and Rich. We are nei­ther web de­sign­ers nor pho­tog­ra­phers. That’s why the de­sign is weird and the pho­tos are kinda meh. Nothing on this site is spon­sored.

Yes, some­one did. Specifically, me (Kenton)! In 2011 I com­pleted a LAN-party op­ti­mized house in Palo Alto, California, and it went vi­ral. It, too, was in col­lab­o­ra­tion with my fa­ther (but I had not yet met Jade).

But con­trary to what most peo­ple think upon see­ing the pic­tures, the orig­i­nal LAN house was not very big: 1400 sqft. This made for a pretty awe­some bach­e­lor pad, but would have been a bit cramped for rais­ing a fam­ily. The new house is much, much bet­ter.

I’ve never heard of any­one else hav­ing done any­thing like this. This sur­prises me! But, surely, if some­one else did it, some­one would have told me about it? If you know of an­other, please let me know!

In 2019, my team at Cloudflare was grow­ing. But, most of the hir­ing was hap­pen­ing in the Austin of­fice, while I worked from San Francisco. Meanwhile, with our first child on the way, Jade and I needed a big­ger house, but we re­ally could not af­ford to buy (much less build) any­thing big­ger in Palo Alto.

I sug­gested to Jade: Should we move to Austin? Jade ini­tially said no, be­cause she wanted our kids to ben­e­fit from Palo Alto’s school dis­trict. At the time, it was rated #12 in the na­tion. But, look­ing closer at the rank­ings re­vealed a sur­prise: The Eanes school dis­trict in Austin was #8. When I showed this to Jade, she changed her mind.

Ironically, just af­ter we moved, covid hit, and Cloudflare be­came 100% re­mote. The orig­i­nal rea­son for the move—be­ing closer to my team—be­came moot. In ret­ro­spect, we could have gone any­where! Not that there’s any­where in par­tic­u­lar that I think would have been bet­ter. It’s just funny.

The 22 game ma­chines (including mon­i­tors, ca­bles, and pe­riph­er­als) cost about $75,000 in to­tal. The house over­all was a 7-digit num­ber. Sorry, I’m not com­fort­able be­ing any more spe­cific than that.

I ac­tu­ally find it funny how cheap com­put­ers are. The cab­i­netry around the game sta­tions cost a sim­i­lar amount to the com­put­ers pow­er­ing them. Think about that! The cab­i­netry is just a bunch of wood, cut into fairly large pieces. Maybe a few screws and hinges. Whereas the com­put­ers in to­tal con­tain more than a tril­lion tran­sis­tors, each of which had to be care­fully etched in the right spot con­nected cor­rectly to all the oth­ers. A tril­lion! That’s 1,000,000,000,000!

Of course, the point is, GPUs are mass-pro­duced. Cabinets for game sta­tions in LAN-party-optimized houses are, um, not.

This ques­tion also makes me un­com­fort­able, but I know from last time that peo­ple will ask it, and if I don’t an­swer, peo­ple will make things up. So, OK, I will tell you.

I (Kenton) started my ca­reer at Google in 2005, which was a pretty good time to be there, even as a ju­nior en­gi­neer. They gave me stock, and that stock went up. With no fam­ily and no hob­bies aside from video games, money piled up in my bank ac­count. After 4-5 years of sav­ing, I was able to make a $200k down pay­ment on a $1M con­struc­tion loan (later con­verted into a mort­gage). In many places that could have bought a man­sion, but in Palo Alto it got me a tiny sliver of land and a 1400 sqft house. Still, I con­sid­ered my­self rich.

Then things got weird. The suc­cess of Google, Facebook, and oth­ers in Silicon Valley had pro­duced a large num­ber of peo­ple in the area with a lot of money, ready to buy houses and start fam­i­lies. Meanwhile, NIMBY poli­cies were block­ing all new de­vel­op­ment. As a re­sult, Palo Alto hous­ing prices, al­ready high, went bonkers over the course of the 2010′s. My house, which had cost me $1M, be­came worth over $2M.

This is ab­solutely un­fair! I built the house so that I could throw par­ties and play video games with my friends. These do not seem like ac­tiv­i­ties that are sup­posed to make money. But it made me a mil­lion dol­lars in profit. What?

So ba­si­cally, we were able to par­lay that into a big­ger house in Austin. And just in time! While Austin hous­ing prices had been grow­ing for a while, they re­ally ex­ploded af­ter 2020. We bought our prop­erty in late 2019. (Aside: Today, in 2024, Austin hous­ing prices are now ac­tu­ally de­clin­ing rapidly, due to an enor­mous amount of new hous­ing hav­ing been built over the last few years. Yes, it can be done! Now is a great time to move to Austin!)

For com­plete­ness, I’ll men­tion two other not-in­signif­i­cant sources of money. First, Jade and I joined Cloudflare in 2017, a cou­ple years be­fore its IPO. This was a good time to join. The stock has done very well, even hit­ting a high point just as we started con­struc­tion. Second, Jade has long been an ac­tive (albeit small-scale) seed-stage in­vestor in star­tups. Before she met me, she in­vested in Matterport, in their very first fund­ing round. They went on to be­come a pub­lic com­pany. We were al­ready in the process of mov­ing to Austin be­fore ei­ther Cloudflare or Matterport went pub­lic, so we did­n’t have any idea at the time how much they’d pay off. But they did, and this al­lowed us to ex­pand scope.

Yes, we are very lucky!

It’s where every­one goes to one place and plays mul­ti­player videogames with each player hav­ing their own com­puter, con­nected over a Local Area Network.

In the 90′s, when in­ter­net con­nec­tions were bad, LAN par­ties were pop­u­lar among PC gamers. But when broad­band got de­cent in the early 2000′s, LAN par­ties largely died off, as peo­ple could now play mul­ti­player games with­out leav­ing the house.

But I think that sucks. For me, LAN par­ties were never just about the game. LAN par­ties are a so­cial event, and the game is merely a cat­a­lyst. LAN par­ties serve very much the same pur­pose as nor­mal par­ties serve for nor­mal peo­ple, but the game makes it eas­ier and more fun for in­tro­verts to be so­cial. Indeed, LAN par­ties are so fun that they tra­di­tion­ally go all night long—much longer than your normie par­ties—be­cause no one wants to stop.

My (Kenton’s) first LAN party was for my 14th birth­day, in 1996. We had four com­put­ers: a 486sx 25Mhz, a 486dx 33Mhz, a 486dx2 50Mhz, and a Pentium 120Mhz. We played Doom 2 all night long. It was the most fun I’d ever had.

That same year, I had an­other LAN party on New Year’s Eve, which I have done every year since. At least two out of three (and usu­ally all three) of my ju­nior high friends from Minneapolis have at­tended every sin­gle time.

In to­tal, I have hosted or at­tended prob­a­bly over 100 LAN par­ties. All of them were at some­one’s house, typ­i­cally with 8-16 peo­ple. I have never been in­ter­ested in big com­mer­cial LAN par­ties with hun­dreds of at­ten­dees—at that point it feels no dif­fer­ent than play­ing with ran­dos on the in­ter­net.

We have an in­ter­net con­nec­tion.

I orig­i­nally thought this too. In fact, my first LAN party house was de­signed to let peo­ple bring their own box and quickly con­nect it to a sta­tion. But no­body ever did. Not once. Some peo­ple brought lap­tops, but they only ever used them if the game sta­tions were all in use al­ready.

I do feel a lot of nos­tal­gia for the days of try­ing to pack four peo­ple, four com­put­ers, and four mon­i­tors into one car on the way to a friends’ LAN party, set­ting up ma­chines on hap­haz­ardly arranged card ta­bles with ques­tion­able seat­ing arrange­ments, daisy-chain­ing power strips and net­work hubs. I’m a lit­tle less nos­tal­gic for the ex­pe­ri­ence of try­ing to copy game files over the net­work to get every­one on the same ver­sion, or pity­ing the one friend who in­evitably has to re­in­stall Windows and does­n’t man­age to get in-game un­til af­ter mid­night.

The fact is that, while these things were fun, they were Type II fun. And they made LAN par­ties in­ac­ces­si­ble. Even the most en­thu­si­as­tic of us did­n’t re­ally want to do all that more than, like, 3-4 times a year, and a lot of peo­ple—even those who like games—re­ally don’t care to do it at all. I’m not even sure if I could do it any­more, as a 40-something with two kids!

With com­put­ers built-in and set up in ad­vance, we can com­mence gam­ing es­sen­tially im­me­di­ately upon enough peo­ple ar­riv­ing. We can get a lot more peo­ple to par­tic­i­pate. If some­one can only drop by for an hour or two, they can still play. And we can do it all much more of­ten: at one point I was host­ing LAN par­ties every other week­end.

Lots of things. We are try­ing new games all the time.

In gen­eral, we pre­fer co­op­er­a­tive games, or at least team games. Most at­ten­dees are not ac­tu­ally hard­core gamers, so skill lev­els vary widely. In a free-for-all com­pet­i­tive game, one or two peo­ple tend to dom­i­nate while sev­eral can’t get any­where—that’s not fun. Cooperative games al­low every­one to par­tic­i­pate ac­cord­ing to their abil­ity. Team com­pet­i­tive games al­low us to care­fully bal­ance the teams, though this can be tricky.

Our fa­vorite LAN game of the past five years is prob­a­bly Deep Rock Galactic, in which the play­ers are a team of space dwarves min­ing an alien planet for re­sources. Prior to Deep Rock, Left 4 Dead 2 served the same pur­pose, or TF2 Mann vs. Machine mode.

We have also played quite a few sur­vival­craft base­builder games, such as Ark or Factorio.

We played a lot of Overwatch, back when it was good, of­ten with us on a team against in­ter­net ran­dos, and oc­ca­sion­ally team-vs-team en­tirely within the house.

We still play Unreal Tournament 2004 reg­u­larly, usu­ally in Assault or Onslaught mode.

No. Sorry, you must be in­vited. I’m sure you un­der­stand: For se­cu­rity rea­sons, we can’t just let ran­dom peo­ple on the in­ter­net into our house.

If you want to get in­vited, you need to fig­ure out some way to get to know one of us, or one of our friends who can vouch for you.

One straight­for­ward (albeit not easy) way to get an in­vite is to get hired at Cloudflare. ;)

No. Everyone logs into their own Steam/Epic/etc. ac­counts, and must buy the game we are play­ing. We do, how­ever, try to pre­in­stall every­thing peo­ple might play. Fortunately, Steam and sim­i­lar game launch­ers are able to use the same copy of the game for all users.

I don’t! I main­tain a sin­gle disk im­age for all the ma­chines. Before the party starts, I will in­stall all needed games and up­dates on that sin­gle disk im­age. The ma­chines all boot off of a net­work drive based on this im­age. Each ma­chine gets a copy-on-write over­lay on top of the main im­age, so that guests can make changes to their ma­chine which won’t be seen by any other, and will be deleted at the end of the party.

I have put all the scripts I use for this up on GitHub.

For the game ma­chines, I mostly tar­geted the Logical Increments “Outstanding” level, which aims to stay just un­der the in­flec­tion point where high-end price goug­ing sets in. To that end:

* CPU: Intel Core i5-13600KF — Games care much more about GPU than CPU.

* CPU heat sink: Scythe Fuma 3 — Mostly cho­sen be­cause it fits in a 4U chas­sis while the Noctua fans do not.

* GPU: Gigabyte Windforce RTX 4070 — Not su­per, not Ti, just 4070

* Motherboard: Gigabyte Z790 Aorus Master — I do not rec­om­mend the moth­er­board! I was aim­ing to get the cheap­est board that had 10G net­work on-board. The only rea­son I needed 10G net­work was be­cause of the net­boot setup: these ma­chines ac­cess their pri­mary stor­age en­tirely over the net­work. Otherwise, you ab­solutely do not need 10G for gam­ing. In gen­eral, I think ex­pen­sive moth­er­boards are a scam: they of­ten pro­vide no real ben­e­fit, but are marked up just be­cause some suck­ers will buy them. Moreover, this par­tic­u­lar moth­er­board is hor­ri­bly un­sta­ble, fre­quently blue-screen­ing shortly af­ter boot. (Luckily, it seems to set­tle down af­ter a minute or two and rarely dis­rupts ac­tual games.)

* RAM: Corsair Vengeance 32GB (2x16GB) DDR5 5600 — Every time I see “Corsair Vengeance” I can’t help but chuckle. Vengeance??? It’s just com­puter mem­ory, dude.

* PSU: Corsair SF750 — Platinum ef­fi­ciency rat­ing ac­tu­ally kinda mat­ters when you’re run­ning 20 of them.

* Storage: Corsair MP700 Gen5 1TB NVMe — The stor­age is not ac­tu­ally used due to the net­boot setup, but my hope is even­tu­ally to im­prove the de­sign such that the copy-on-write over­lay can be on lo­cal disk in­stead of server-side, us­ing this stor­age.

* Chassis: Rosewill RSV-L4500U 4U — Realistically if you’re rack-mount­ing con­sumer-grade hard­ware you have to go with a 4U chas­sis. I re­ally tried to make 2U or even 3U work. It does­n’t work.

* Keyboard: Logitech K120 Wired — The world’s cheap­est key­board at $13 a pop. Works per­fectly fine for all gam­ing needs. (See next ques­tion, be­low.)

* Mouse: Logitech M500s Wired — A cheap 5-button mouse. Unfortunately I’ve found the mid­dle but­ton is dif­fi­cult to use with­out ac­ci­den­tally scrolling. I miss the old MX518.

* Sound bar: Soulion R30 Wired — This is just some crap I found on Amazon with­out do­ing a lot of re­search, but they seem to work fine. Unfortunately the mon­i­tors don’t have built-in speak­ers, but this sound bar is prob­a­bly bet­ter than a typ­i­cal built-in speaker, so in the end I’m happy with it.

Also, in case you are won­der­ing:

* Workstation mon­i­tor: Samsung 57″ Odyssey Neo G9 Dual 4K — Ironically, I use this for work, not games. It’s great for cod­ing. Playing games on it gives me ver­tigo.

To be hon­est, when I’ve used more-ex­pen­sive “gaming” key­boards and mice I have never ac­tu­ally liked them. I mean, they are fine, but I don’t feel like I get any ben­e­fit. If any­thing there are draw­backs: they tend to have ex­tra but­tons that en­able gim­micky fea­tures which only mess me up when I touch one of those but­tons by ac­ci­dent. And they tend to be loaded with RGB, which I just don’t care about. So I see no rea­son to spend money on any of that.

Note that for work pur­poses, I ab­solutely need a bet­ter key­board. (I use a Kinesis Advantage 360.) But for WASD pur­poses, the cheap­est pos­si­ble key­board is all I want. When it comes to mice, for ei­ther work or gam­ing, I want some­thing that has five but­tons and fits rea­son­ably in my (large) hand but that’s all.

With all that said, guests are wel­come to bring their own key­boards and mice if they like. Each sta­tion has a USB hub where you can plug in your fa­vorite pe­riph­er­als.

Honestly I never even thought about it. I haven’t used a mousepad in decades. None of my friends ever com­mented on it. But I guess it might be a good idea, to pre­vent wear on the wood fin­ish.

OK, yeah, this was a mis­take.

I’m a soft­ware guy, and my ex­pe­ri­ence with phys­i­cal net­work­ing is lim­ited to homes. Before I posted this site, I hon­estly did­n’t know what a “patch panel” was.

The sub­con­trac­tor who pulled all the cat6 ca­ble in the house was some­one who does AV sys­tems in houses, not com­mer­cial net­work­ing. He was cho­sen by my gen­eral con­trac­tor, who also ob­vi­ously spe­cial­izes in houses. He was a good guy! But in ret­ro­spect, given the scope, it might have made sense for me to in­sist on find­ing a net­work con­trac­tor that nor­mally does com­mer­cial build­ings. Anyway, the guy asked if I wanted him to crimp the ca­bles, and I said “uhh well I cer­tainly don’t want to do it, so yeah?”, and so he did. I don’t think he men­tioned patch pan­els, or if he did, I did­n’t un­der­stand what he meant. Then when I moved in, I mounted these Unifi switches, shoved all ca­bles into them, and called it a day.

I now un­der­stand that I should have asked the con­trac­tor to ter­mi­nate all the cat6 into “patch pan­els”, that is, rows of RJ45 sock­ets. I could then use patch ca­bles to con­nect those to the ac­tual switches. This way, the in-wall ca­bles never move at all, there­fore are at min­i­mal risk of be­ing dam­aged some­how. Also, I could nicely la­bel each one, and eas­ily re­con­fig­ure what is con­nected to what. I wish I’d done that!

That said, in prac­tice I mostly don’t have a need to treat any of these ca­bles spe­cially (except that the PoE de­vices need to be con­nected to the PoE switch). I’m happy man­ag­ing my net­work en­tirely in soft­ware.

By the way, the game ma­chines are not ac­tu­ally con­nected to the switches in the photo. There is a sep­a­rate USW EnterpriseXG 24 fur­ther down the rack, pro­vid­ing 10G net­work­ing to those ma­chines (and al­low­ing them to uti­lize the full 2G in­ter­net band­width).

The long DisplayPort and USB ca­bles range from 35 to 100 feet, de­pend­ing on the spe­cific lo­ca­tion. All ca­bles are Monoprice SlimRun, which are fiber op­tic. The speed of a sig­nal in fiber op­tic ca­ble is about 2/3 the speed of light, and light trav­els at about 1 foot per nanosec­ond, so 100 feet of fiber would add about 150ns of la­tency. Thats 0.00015ms. Wheras at 144Hz, you see one frame per 7ms. In other words, no, the ca­ble length does not add any mean­ing­ful la­tency. (For what it’s worth, sig­nal prop­a­ga­tion in cop­per ca­bles is sim­i­larly fast, but high-band­width sig­nals in cop­per tend to de­grade more quickly over long dis­tance.)

Frankly, it would cost more, per­form worse, and I’m not even sure how to set it up. Games are re­source-in­ten­sive. A high-end game will fully uti­lize the ma­chine’s GPU, CPU, and RAM, so there’s no real ef­fi­ciency to be gained by pack­ing more play­ers onto fewer ma­chines. If you wanted to put four play­ers on one ma­chine—if the soft­ware even ex­ists to make it work—you’d need a ma­chine with 4x the cores, 4x the RAM, and prob­a­bly four sep­a­rate GPUs. To do that you have to dive into “enterprise” hard­ware that gets ex­tremely ex­pen­sive. Building four sep­a­rate ma­chines is ac­tu­ally cheaper, and does­n’t re­quire any spe­cial vir­tu­al­iza­tion layer.

Generally, I try to avoid any cloud-de­pen­dent home au­toma­tion.

For se­cu­rity cam­eras, we use UniFi Protect. I am very happy with these. They will re­li­ably wake me up if a hu­man ap­proaches my house in the mid­dle of the night, with very few false pos­i­tives.

I wrote my own baby mon­i­tor that sim­ply com­bines the au­dio from two UniFi cam­eras placed near my kids’ beds and makes the stream avail­able via a web page. I like it much bet­ter than the off-the-shelf mon­i­tors we were us­ing be­fore!

I in­tend to set up Home Assistant even­tu­ally, but haven’t got­ten around to it yet.

Yes, but not be­cause of the com­put­ers. The com­put­ers are off most of the time; I only turn them on for par­ties. Most of our en­ergy us­age goes to heat­ing and cool­ing. We have ef­fi­cient heat pumps and so­lar pan­els, but it’s still a dis­turb­ing amount of en­ergy us­age and some­thing I’m try­ing to de­bug. Perhaps we have too many win­dows let­ting in too much sun­light…

We had a sub­con­trac­tor de­sign­ing the HVAC sys­tem. I told him that there needed to be a ded­i­cated air con­di­tioner for the server rack. He sort of rolled his eyes and said sure.

Later, when I got the de­sign, there was no AC for the server rack. We had a con­ver­sa­tion:

Me: Where’s the AC for the server rack? We re­ally do need AC in there.

Him: I mean, how many servers do you have?

Me: Well, if all the ma­chines are run­ning at full power play­ing a high-fi­delity game, they could be con­sum­ing 15kW of power and turn­ing it all into heat.

Him: (skeptical) That would be by far the largest server rack we’ve ever seen in a res­i­den­tial set­ting.

Me: I would ex­pect so, yes.

Our phi­los­o­phy with the cat doors is that we want to be able to close our bed­room doors while still al­low­ing cats to en­ter. If we locked our cat out of our bed­room, he would meow all night long, and worse, we would­n’t get cud­dles. But, leav­ing the bed­room door open sac­ri­fices pri­vacy. Solution: Cats get their own doors.

Pretty of­ten! I try to ex­er­cise most days and al­ter­nate be­tween DDR, bik­ing, and swim­ming. Of these, DDR re­ally has the best fun/​work and work/​time ra­tios. Jade plays, too. I’ve been play­ing for over 20 years but my skill plateaued a while ago at “not quite com­pet­i­tive” lev­els…

There are some ob­scure ver­sions of DDR, and an old un­of­fi­cial build of Stepmania, that sup­ports four pads. I haven’t ac­tu­ally got­ten around to try­ing them yet, but I in­tend to at some point, and if I end up hav­ing to make my own Stepmania fork, so be it. I’ve been think­ing about an al­go­rithm to con­vert “doubles” step charts into “quads”, where one per­son uses all four pads.

A com­mu­nity vote in the CSS-Next repos­i­tory on GitHub de­cided on a new of­fi­cial logo for CSS. The de­sign fol­lows the de­sign lan­guage of the lo­gos of other web tech­nolo­gies like JavaScript, TypeScript, and WebAssembly.

But per­haps more im­por­tantly, the logo uses the color re­bec­ca­pur­ple (#663399), a color that was added to the CSS spec­i­fi­ca­tion in 2014 in honor of Eric Meyer’s daugh­ter, Rebecca, who passed away at the age of six on her birth­day from brain can­cer.

Eric Meyer, au­thor of sev­eral books on CSS, has been an im­por­tant fig­ure in the CSS com­mu­nity since the late 1990s.

The color was orig­i­nally go­ing to be called bec­ca­pur­ple, but Meyer asked that it in­stead be named re­bec­ca­pur­ple, as his daugh­ter had wanted to be called Rebecca once she had turned six. She had said that Becca was a “baby name,” and that once she had turned six, she wanted to be called Rebecca. As Eric Meyer put it, “She made it to six. For al­most twelve hours, she was six. So Rebecca it is and must be.”

* O2 has cre­ated hu­man-like AI ‘Granny’ to an­swer calls in real time from fraud­sters, keep­ing them on the phone and away from cus­tomers for as long as pos­si­ble

* Trained us­ing cut­ting-edge tech­nol­ogy and real scam­baiter con­tent, life­like ‘Daisy’ is in­dis­tin­guish­able from a real per­son, fool­ing scam­mers into think­ing they’ve found a per­fect tar­get when re­ally, she’s beat­ing them at their own hor­ri­ble game

* Former Love Islander and scam vic­tim, Amy Hart, is work­ing with ‘Daisy’ and has made a shock­ing new video to ex­pose fraud­sters’ crooked tac­tics and help O2 cus­tomers swerve the scam­mers

* With Daisy re­veal­ing how you’re not al­ways speak­ing to the per­son you think you are, O2 is urg­ing cus­tomers to re­main vig­i­lant, leave ‘scambaiting’ to the AI ex­perts and re­port sus­pected fraud­u­lent calls and texts for free to 7726

O2 has to­day un­veiled the newest mem­ber of its fraud pre­ven­tion team, ‘Daisy’. As ‘Head of Scammer Relations’, this state-of-the-art AI Granny’s mis­sion is to talk with fraud­sters and waste as much of their time as pos­si­ble with hu­man-like ram­bling chat to keep them away from real peo­ple, while high­light­ing the need for con­sumers to stay vig­i­lant as the UK faces a fraud epi­demic.

Created us­ing a range of cut­ting-edge AI tech­nol­ogy and trained with the help of one of YouTube’s best known scam­baiters, Jim Browning, Daisy is a life­like AI Granny com­pletely in­dis­tin­guish­able from a real per­son. Able to in­ter­act with scam­mers in real time with­out any in­put from her cre­ators, O2 has put Daisy to work around the clock an­swer­ing dodgy calls.

Daisy com­bines var­i­ous AI mod­els which work to­gether to lis­ten and re­spond to fraud­u­lent calls in­stan­ta­neously and is so life­like it has suc­cess­fully kept nu­mer­ous fraud­sters on calls for 40 min­utes at a time.

As part of Virgin Media O2’s on­go­ing “Swerve the Scammers” cam­paign, Scambaiter Daisy has been cre­ated in re­sponse to new re­search from O2 re­veal­ing 7 in 10 (71%) of Brits would like to get their own back against scam­mers that have tried to trick them or their loved ones. However, not want­ing to waste their own time ranked as the top rea­son why the pub­lic would­n’t bait scam­mers them­selves (53%).

With more than two thirds of Brits (67%) con­cerned about be­ing the tar­get of fraud and one in five (22%) ex­pe­ri­enc­ing a fraud at­tempt every sin­gle week, O2 is fight­ing back.

After sev­eral weeks of tak­ing calls in the run up to International Fraud Awareness Week (November 17-23), the AI Scambaiter has told frus­trated scam­mers me­an­der­ing sto­ries of her fam­ily, talked at length about her pas­sion for knit­ting and pro­vided ex­as­per­ated callers with false per­sonal in­for­ma­tion in­clud­ing made-up bank de­tails. By trick­ing the crim­i­nals into think­ing they were de­fraud­ing a real per­son and play­ing on scam­mers bi­ases about older peo­ple, Daisy has pre­vented them from tar­get­ing real vic­tims and, most im­por­tantly, has ex­posed the com­mon tac­tics used so cus­tomers can bet­ter pro­tect them­selves

Influencer and re­al­ity TV star, Amy Hart, has worked with Daisy to pro­duce a shock­ing video to show how she’s tak­ing on phoney fraud­sters like the one who tar­geted her. After re­ceiv­ing a call from some­one who said they were call­ing from her bank on the morn­ing of her friend’s wed­ding, Amy fell vic­tim to a scam which saw more than £5,000 drained from her bank ac­count in a mat­ter of min­utes.

The har­row­ing ex­pe­ri­ence has left Amy pas­sion­ate about spread­ing the word on scams and ex­pos­ing their tac­tics to help keep oth­ers safe. Watch the video here.

Amy Hart said “I know first-hand just how so­phis­ti­cated nasty fraud­sters can be, that’s why I’ve teamed up with O2 and AI Scambaiter Daisy to take the fight back to them, keep­ing them busy with calls go­ing nowhere.

“But whilst I love a wind up, it’s scary to see the lengths scam­mers go to steal every­thing from pass­words to bank de­tails re­gard­less of who they’re speak­ing to. Whether you’re young or old, any­one can be a vic­tim of a scam that’s why we can never be too care­ful when it comes to un­ex­pected calls or texts.

“If you have even the tini­est doubt about who you’re speak­ing to, the best thing to do is to hang up the phone and call back on a trusted num­ber.”

Murray Mackenzie, Director of Fraud at Virgin Media O2, said: “We’re com­mit­ted to play­ing our part in stop­ping the scam­mers, in­vest­ing in every­thing from fire­wall tech­nol­ogy to block out scam texts to AI-powered spam call de­tec­tion to keep our cus­tomers safe.

“The newest mem­ber of our fraud-pre­ven­tion team, Daisy, is turn­ing the ta­bles on scam­mers — out­smart­ing and out­ma­noeu­vring them at their own cruel game sim­ply by keep­ing them on the line.

“But cru­cially, Daisy is also a re­minder that no mat­ter how per­sua­sive some­one on the other end of the phone may be, they aren’t al­ways who you think they are. With scam­mers op­er­at­ing full­time call cen­tres specif­i­cally to tar­get Brits, we’re urg­ing every­one to re­main vig­i­lant and help play their part in stop­ping fraud by for­ward­ing on dodgy calls and texts to 7726 for free.”

O2 has in­vested heav­ily in the fight against fraud, rolling out AI-powered spam fight­ing tools and new caller iden­ti­fi­ca­tion ser­vices free to all mo­bile cus­tomers to help pro­tect them. The op­er­a­tor also blocks mil­lions of fraud­u­lent texts and calls from reach­ing cus­tomers phones every month.

However, with scam­mers con­stantly evolv­ing their processes and us­ing in­creas­ingly so­phis­ti­cated meth­ods, the busi­ness is en­cour­ag­ing Brits to leave scam­bait­ing to the AI ex­perts. Instead, the pub­lic can help block scam­mers by for­ward­ing sus­pected scam calls and text mes­sages to 7726.

By re­port­ing dodgy calls and mes­sages, the tele­coms com­pany is able to in­ves­ti­gate and block the mo­bile num­bers used by fraud­sters and can also use scam texts to help re­fine its block­ing ser­vices, mak­ing it eas­ier to iden­tify and stop new trends faster in fu­ture. Last year alone, Virgin Media O2 blocked 89 mil­lion texts, in part thanks to 7726.

To help make life eas­ier for cus­tomers, O2 has pulled to­gether a new web­page of­fer­ing tips, tricks and ad­vice so they know what to look out for. Head to our Swerve the Scammers page for more in­for­ma­tion.

Virgin Media O2 is call­ing for wider ac­tion to pre­vent fraud

The com­pany re­cently ex­posed the scale of the UK’s fraud prob­lem af­ter find­ing that nearly seven in ten Brits (69%)1 re­ported that they’ve been tar­geted by scam­mers. Last year alone, Virgin Media O2 in­ter­cepted and blocked over £250 mil­lion in sus­pected fraud­u­lent trans­ac­tions — equiv­a­lent to stop­ping one every two min­utes.

Warning that not enough is be­ing done to pro­tect con­sumers, Virgin Media O2 is call­ing on the gov­ern­ment to take ac­count­abil­ity for stop­ping fraud at its source by ap­point­ing a ded­i­cated fraud min­is­ter and cre­at­ing a sin­gle cen­tralised, spe­cialised and prop­erly re­sourced na­tional polic­ing body re­spon­si­ble for in­ves­ti­gat­ing all in­stances of fraud.

Daisy is a hu­man-like AI that has been de­vel­oped to hold au­tonomous con­ver­sa­tions with scam callers and keep them on the line for as long as pos­si­ble. The cus­tom-built AI scam­baiter has been an­swer­ing calls from scam­mers and hav­ing life­like but me­an­der­ing con­ver­sa­tions with no in­put re­quired from her cre­ators.

Daisy com­bines var­i­ous AI mod­els which work to­gether to first lis­ten to the caller and tran­scribe their voice into text. Appropriate re­sponses are then gen­er­ated through a cus­tom large lan­guage model com­plete with a char­ac­ter ‘personality’ layer, and then fed back through a cus­tom AI text-to-speech model to gen­er­ate a voice an­swer. This takes place in real time, al­low­ing the tool to hold a hu­man-like con­ver­sa­tion with a caller.

O2 has pulled to­gether three sim­ple steps on what to do when called by a scam­mer or upon re­ceiv­ing a sus­pi­cious mes­sage:

STOP: If you re­ceive a call out of the blue for some­one claim­ing to be from O2, think about what you’re be­ing asked to do. Does it feel right? Are you be­ing asked for per­sonal data or a code over the phone? If you have any sus­pi­cion that you might be speak­ing to a scam­mer, the best thing to do is hang up and call us back by di­alling 202 from your O2 phone.

SEND to 7726: Worked out you might have spo­ken to or re­ceived a text from a scam­mer? Don’t just ig­nore it, take a few sec­onds to for­ward on to 7726. It spells SPAM on your phone’s key­pad and is the free num­ber to use to re­port to us so we can in­ves­ti­gate. It helps keep you safe and al­lows us to block fraud­sters num­bers and pre­vent or shut down sim­i­lar scams faster in fu­ture.

SPEAK OUT: Let your friends and fam­ily know about the scam. By telling oth­ers, you can help keep them safe and en­sure they’re never caught off guard.

Read more about Virgin Media O2’s call for struc­tural re­form to ad­dress the UK’s fraud epi­demic here.

Strand Partners’ spe­cial­ist re­search team con­ducted an on­line sur­vey of 5,247 mem­bers of the UK pub­lic be­tween 07.06.24 — 19.06.24. The sam­ple is rep­re­sen­ta­tive by gen­der, age and NUTs 1 re­gion, ed­u­ca­tion, and in­come against the most re­cent ONS cen­sus data.

A year ago, there was a lot of talk about large lan­guage mod­els (LLMs) play­ing chess. Word was that if you trained a big enough model on enough text, then you could send it a par­tially played game, ask it to pre­dict the next move, and it would play at the level of an ad­vanced am­a­teur.

This seemed im­por­tant. These are “language” mod­els, af­ter all, de­signed to pre­dict lan­guage.

Now, mod­ern LLMs are trained on a size­able frac­tion of all the text ever cre­ated. This surely in­cludes many chess games. But they weren’t de­signed to be good at chess. And the games that are avail­able are just lists of moves. Yet peo­ple found that LLMs could play all the way through to the end game, with never-be­fore-seen boards.

Did the lan­guage mod­els build up some kind of in­ter­nal rep­re­sen­ta­tion of board state? And how to con­struct that state from lists of moves in chess’s ex­tremely con­fus­ing no­ta­tion? And how valu­able dif­fer­ent pieces and po­si­tions are? And how to force check­mate in an end-game? And they did this all “by ac­ci­dent”, as part of their goal of pre­dict­ing gen­eral text?

If lan­guage mod­els can do all that for chess, then maybe it’s a hint of how they deal with other sit­u­a­tions too.

So that was very ex­cit­ing. A year ago.

Since then, there’s mostly been si­lence. So I de­cided to check in and see how things are go­ing. Having done that, I can now re­port: Weirdly.

To make LLMs play chess, I sent them prompts like this:

You are a chess grand­mas­ter.

Please choose your next move.

Use stan­dard al­ge­braic no­ta­tion, e.g. “e4” or “Rdf8″ or “R1a3”.

NEVER give a turn num­ber.

NEVER ex­plain your choice.

Here is a rep­re­sen­ta­tion of the po­si­tion:

[Event “Shamkir Chess”]

[White “Anand, Viswanathan”]

[Black “Topalov, Veselin”]

[Result “1-0”]

[WhiteElo “2779”]

[BlackElo “2740”]

1. e4 e6 2. d3 c5 3. Nf3 Nc6 4. g3 Nf6 5.

I used the out­put as a move. I al­ways had the LLM play as white against Stockfish—a stan­dard chess AI—on the low­est dif­fi­culty set­ting.

The first model I tried was llama-3.2-3b. This is a “base model”, mean­ing it is mostly trained to out­put text, not to chat with you or obey in­struc­tions. It’s quite small by mod­ern stan­dards, with only 3 bil­lion pa­ra­me­ters. For ref­er­ence, GPT-2, re­leased back in 2019, had 1.5 bil­lion pa­ra­me­ters, and GPT-4 is ru­mored to have around 1.8 tril­lion.

I had it play 50 games, then had a chess en­gine score each board af­ter each turn in “centipawns”. This is a mea­sure where a pawn is 100 points, but there’s also ac­count­ing for po­si­tion. If the game was over, I as­signed a score of +1500 if the LLM won, 0 if there was a tie, and -1500 if it lost.

In the above fig­ure, there’s one line for each game, and the dark line shows the per-turn me­dian. The LLM can play stan­dard open­ings for a few moves but then quickly starts throw­ing away pieces. It lost every sin­gle game, even though Stockfish was on the low­est set­ting.

Maybe that model is too small? So I got llama-3.1-70b, which is a sim­i­lar model but with 70 bil­lion pa­ra­me­ters in­stead of 3 bil­lion. The re­sults were:

A lit­tle bet­ter, but still ex­tremely bad. Next I tried llama-3.1-70b-in­struct, a sim­i­lar model, ex­cept trained to be bet­ter at fol­low­ing in­struc­tions. The re­sults were:

Maybe there’s some­thing wrong with the Llama mod­els or datasets? So I tried Qwen-2.5-72b.

Maybe Qwen is some­how de­fec­tive too? So I tried com­mand-r-v01, a 35 bil­lion pa­ra­me­ter model.

And then I tried gemma-2-27b.

And then I tried gpt-3.5-turbo-in­struct. This is a closed OpenAI model, so de­tails are very murky. I only ran 10 tri­als since AI com­pa­nies have in­ex­plic­a­bly ne­glected to send me free API keys and this was cost­ing The Automator money. The re­sults were:

Even if you raise Stockfish’s level a few clicks, this model will still win every game.

Moving on… I next tried gpt-3.5-turbo, a model that’s sim­i­lar, ex­cept tuned to be more chatty and con­ver­sa­tional.

And then I tried gpt-4o-mini, which is a newer chat model.

And then I tried gpt-4o, a big­ger chat model.

It lost every sin­gle game, though it lost slightly slower.

Finally, I tried o1-mini, a model that’s sup­posed to be able to solve com­plex tasks. (I’m too poor for o1.)

Notice any­thing? Any pat­terns jump out at you?

There are lots of peo­ple on the in­ter­net who have tried to get LLMs to play chess. The his­tory seems to go some­thing like this:

* Before September 2023: Wow, re­cent LLMs can sort of play chess! They fall apart af­ter the early game, but they can do some­thing! Amazing!

* September-October 2023: Wow! LLMs can now play chess at an ad­vanced am­a­teur level! Amazing!

* Recently: Wow, re­cent LLMs can sort of play chess! They fall apart af­ter the early game, but they can do some­thing! Amazing!

I can only as­sume that lots of other peo­ple are ex­per­i­ment­ing with re­cent mod­els, get­ting ter­ri­ble re­sults, and then mostly not say­ing any­thing. I haven’t seen any­one say ex­plic­itly that only gpt-3.5-turbo-in­struct is good at chess. No other LLM is re­motely close.

To be fair, a year ago, many peo­ple did no­tice that gpt-3.5-turbo-in­struct was much bet­ter than gpt-3.5-turbo. Many spec­u­lated at the time that this is be­cause gpt-3.5-turbo was sub­ject to ad­di­tional tun­ing to be good at chat­ting.

That might be true. Here’s a com­par­i­son of three mod­els where we have sim­i­lar ver­sions with or with­out ad­di­tional chat tun­ing.

In all cases, ad­di­tional in­struc­tion tun­ing makes the model worse. But the dif­fer­ence is very small in two cases, and enor­mous in the other.

I can think of four pos­si­ble ex­pla­na­tions.

Theory 1: Base mod­els at suf­fi­cient scale can play chess, but in­struc­tion tun­ing de­stroys it.

This would be con­sis­tent with our data. But I did man­age to get llama-3.1-405b to play a cou­ple games. Despite be­ing larger than gpt-3.5-turbo, it was still ter­ri­ble.

Theory 2: GPT-3.5-instruct was trained on more chess games.

All mod­els were clearly trained on a lot of chess games. But it’s hard to know ex­actly how many.

Theory 3: There’s some­thing par­tic­u­lar about dif­fer­ent trans­former ar­chi­tec­tures.

I doubt this, but it could be that for some rea­son, Llama type mod­els are uniquely bad at chess.

Theory 4: There’s “competition” be­tween dif­fer­ent types of data.

We know that trans­form­ers trained specif­i­cally on chess games can be ex­tremely good at chess. Maybe gpt-3.5-turbo-in­struct hap­pens to have been trained on a higher frac­tion of chess games, so it de­cided to ded­i­cate a larger frac­tion of its pa­ra­me­ters to chess.

That is, maybe LLMs sort of have lit­tle “chess sub­net­works” hid­den in­side of them, but the size of the sub­net­works de­pends on the frac­tion of data that was chess. (If this the­ory were true, we should prob­a­bly ex­pect that big enough model should be­come good at chess, pro­vided they are trained on enough chess games, even if the frac­tion of chess games is low.)

I did things this way (i.e. by work­ing with stan­dard al­ge­braic no­ta­tion) be­cause this is how peo­ple got good re­sults two years ago, and in pre­lim­i­nary ex­per­i­ments I also found it to work best.

If you want to know ex­actly how I did things, here are some words: I ran all the open mod­els (anything not from OpenAI, mean­ing any­thing that does­n’t start with gpt or o1) my­self us­ing Q5_K_M quan­ti­za­tion, what­ever that is. For the open mod­els I man­u­ally gen­er­ated the set of le­gal moves and then used gram­mars to con­strain the mod­els, so they al­ways gen­er­ated le­gal moves. Since OpenAI is lame and does­n’t sup­port full gram­mars, for the closed (OpenAI) mod­els I tried gen­er­at­ing up to 10 times and if it still could­n’t come up with a le­gal move, I just chose one ran­domly. For the chat mod­els llama-3.1-70b-in­struct, gemma-2-27b-it, gpt-3.5-turbo, gpt-4o-mini, and gpt-4o I changed the sys­tem prompt to “You are a chess grand­mas­ter. You will be given a par­tially com­pleted game. After see­ing it, you should choose the next move.” It’s im­pos­si­ble to change the sys­tem prompt for o1-mini, so I did­n’t. I used a tem­per­a­ture of 0.7 for all the open mod­els and the de­fault for the closed (OpenAI) mod­els. The fact that OpenAI has “open” as part of their name sure made this para­graph hard to write.

One ex­tremely strange thing I no­ticed was that if I gave a prompt like “1. e4 e5 2. ” (with a space at the end), the open mod­els would play much, much worse than if I gave a prompt like “1 e4 e5 2.” (without a space) and let the model gen­er­ate the space it­self. Huh?

After some con­fu­sion, I’m pretty sure this is be­cause of the to­k­enizer. Look at how the Llama to­k­enizer breaks up a string of moves:

After the “1.”, it gen­er­ates “ e” as a sin­gle to­ken. That’s not the same as hav­ing a space fol­lowed by an e. So putting in the space and ask­ing mod­els to gen­er­ate to­kens pre­sents the model with a con­fus­ing sit­u­a­tion and leads to bad pre­dic­tions.

The right way to deal with this is “token heal­ing”—to delete the last to­ken of the in­put and then do con­strained gen­er­a­tion over all strings that start with the deleted stuff. But I could­n’t fig­ure out any easy way to do that. So, in­stead I left the space out and mod­i­fied the gram­mar so that the model could gen­er­ate a space (or not), then one of the cur­rent le­gal moves, and then an­other space (or not). Fun times!

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We res­cued these old demos from the hard dri­ves of an­cient com­put­ers scat­tered around the of­fice, and are of­fer­ing them up as high qual­ity videos:

Also known as the “Free TVs” demo, this was shown at the SIGGRAPH com­puter graph­ics con­fer­ence, hot on the heels of the re­lease of the orig­i­nal Half-Life. This is the high­est qual­ity video we’ve still got from this era of Half-Life 2’s de­vel­op­ment.

We built this demo to bring to E3 a year ear­lier, and then de­cided at the last minute we weren’t ready to show the game. 20 years later, we’re okay with you see­ing this stuff.

The demo that re­vealed Half-Life 2 and the Source en­gine to the world. This was pre­vi­ously only avail­able as shaky­cam recorded from our E3 booth, now avail­able as di­rect cap­ture.

We res­cued these old demos from the hard dri­ves of an­cient com­put­ers scat­tered around the of­fice, and are of­fer­ing them up as high qual­ity videos:

Also known as the “Free TVs” demo, this was shown at the SIGGRAPH com­puter graph­ics con­fer­ence, hot on the heels of the re­lease of the orig­i­nal Half-Life. This is the high­est qual­ity video we’ve still got from this era of Half-Life 2’s de­vel­op­ment.

We built this demo to bring to E3 a year ear­lier, and then de­cided at the last minute we weren’t ready to show the game. 20 years later, we’re okay with you see­ing this stuff.

The demo that re­vealed Half-Life 2 and the Source en­gine to the world. This was pre­vi­ously only avail­able as shaky­cam recorded from our E3 booth, now avail­able as di­rect cap­ture.

The demo that re­vealed Half-Life 2 and the Source en­gine to the world. This was pre­vi­ously only avail­able as shaky­cam recorded from our E3 booth, now avail­able as di­rect cap­ture.

We built this demo to bring to E3 a year ear­lier, and then de­cided at the last minute we weren’t ready to show the game. 20 years later, we’re okay with you see­ing this stuff.

Also known as the “Free TVs” demo, this was shown at the SIGGRAPH com­puter graph­ics con­fer­ence, hot on the heels of the re­lease of the orig­i­nal Half-Life. This is the high­est qual­ity video we’ve still got from this era of Half-Life 2’s de­vel­op­ment.

It’s a Panzer IVD of the 31st Panzer Regiment as­signed to the 5th Panzer Div. com­manded by Lt. Heinz Zobel lost on May 13th, 1940. The “lake” is the Meuse River. The man is a German pi­o­neer.

All credit to find­ing the Panzer of the Lake goes to ConeOfArc for co­or­di­nat­ing the search, and miller786 and their team for find­ing the Panzer. Full sources and de­tails are in Panzer Of The Lake - Meuse River Theory

The photo was taken about co­or­di­nates 50.29092467073664, 4.893099128823844 near mod­ern Wallonia, Belgium on the Meuse River. The tank was not re­cov­ered un­til much later in 1941. The man is an un­named German pi­o­neer likely at the time of re­cov­ery.

Comparison of an al­ter­na­tive orig­i­nal photo and the most re­cent im­age avail­able of the lo­ca­tion (July 2020, Google Street View)

On May 12th, 1940 the 31st Panzer Regiment, as­signed to the 5th Panzer Division, at­tempted to cap­ture a bridge over the Meuse River at Yvoir. The bridge was de­mol­ished by 1st Lieutenant De Wispelaere of the Belgian Engineers.

Werner Advance Detachment (under Oberst Paul Hermann Werner, com­man­der, 31st Panzer Regiment), which be­longed to the 5th Panzer Division, un­der Rommel’s com­mand… Werner re­ceived a mes­sage from close sup­port air re­con­nais­sance in the af­ter­noon that the bridge at Yvoir (seven kilo­me­ters north of Dinant) was still in­tact. He (Werner) im­me­di­ately or­dered Leutnant [Heinz] Zobel’s ar­mored as­sault team of two ar­mored scout cars and one Panzer pla­toon to head to the bridge at top speed… Belgian en­gi­neers un­der the com­mand of 1st Lieutenant de Wispelaere had pre­pared the bridge for de­mo­li­tion while a pla­toon of Ardennes Light Infantry and el­e­ments of a French in­fantry bat­tal­ion screened the bridge… Although the last sol­diers had al­ready passed the bridge, de Wispelaere de­layed the de­mo­li­tion be­cause civil­ian refugees were still ap­proach­ing… two German ar­mored scout cars charged to­ward the bridge while the fol­low­ing three Panzers opened fire. De Wispelaere im­me­di­ately pushed the elec­tri­cal ig­ni­tion, but there was no ex­plo­sion… Wispelaere now left his shel­ter and worked the man­ual ig­ni­tion de­vice. Trying to get back to his bunker, he was hit by a burst from a German ma­chine gun and fell to the ground, mor­tally wounded. At the same time, the ex­plo­sive charge went off. After the gi­gan­tic smoke cloud had drifted away, only the rem­nants of the pil­lars could be seen.

A few kilo­me­ters south at Houx, the Germans used a por­tion of a pon­toon bridge (Bruckengerat B) rated to carry 16 tons to ferry their 25 ton tanks across.

By noon on May 13, Pioniere com­pleted an eight-ton ferry and crossed twenty anti-tank guns to the west bank, how­ever to main­tain the tempo of his di­vi­sions ad­vance, he needed ar­mor and mo­tor­ized units across the river. Rommel per­son­ally or­dered the ferry con­verted to a heav­ier six­teen-ton vari­ant to fa­cil­i­tate the cross­ing of the light Panzers and ar­mored cars. Simultaneously, the Pioniere be­gan con­struc­tion on a bridge ca­pa­ble of cross­ing the di­vi­sion’s heav­ier Panzers and mo­tor­ized units.

Major Erich Schnee in “The German Pionier: Case Study of the Combat Engineer’s Employment During Sustained Ground Combat”

On the evening of the 13th, Lt. Zobel’s tank is cross­ing. Approaching the shore, the ferry lifts, the load shifts, and the tank falls into the river.

The panzer IV of Lieutenant Zabel [sic] of the 31. Panzer Regiment of the 5. Panzer-Division, on May 13, 1940, in Houx, as good as un­der­wa­ter ex­cept for the ve­hi­cle com­man­der’s cupola. Close to the west bank, at the pon­toon cross­ing site and later site of 5. Panzer Division bridge, a 16 tonne ferry (Bruckengerat B) gave way to the ap­proach­ing shore­line, likely due to the ro­tat­ing move­ment of the panzer, which turned right when dis­em­bark­ing (the only pos­si­ble di­rec­tion to quickly leave the Meuse’s shore due to the wall cre­ated by the rail line). The tank would be fished out in 1941 dur­ing the re­con­struc­tion of the bridge.

Sometime later the pho­to­graph was taken of a German pi­o­neer in­fantry­man look­ing at the tank. Later the tank was re­cov­ered and its ul­ti­mate fate is un­known.

Available ev­i­dence sug­gests the sol­dier in the photo is a Pioneer/Tank re­cov­ery crew, hold­ing a Kar98k and wear­ing an EM/NCO’S Drill & Work uni­form, more com­monly known as “Drillich”.

His role is proven by the pres­ence of pon­toon fer­ries on the Meuse river, used by the 5th Panzer Division. That is also proven by his uni­form, which, as ev­i­dence sug­gests, was used dur­ing work to pre­vent dam­age to their stan­dard woolen uni­form.

An early ver­sion of the Drillich

While I can’t iden­tify the photo, I can nar­row down the tank. I be­lieve it is a Panzer IV D.

It has the short bar­relled 7.5 cm KwK 37 nar­row­ing it down to a Panzer IV Ausf. A through F1 or a Panzer III N.

Both had very sim­i­lar tur­rets, but the Panzer III N has a wider gun mant­let, a more an­gu­lar shroud, and lacked (or cov­ered) the dis­tinc­tive an­gu­lar view ports (I be­lieve they’re view ports) on ei­ther side of the tur­ret face.

This leaves the Panzer IV. The dis­tinc­tive cupola was added in model B. The ex­ter­nal gun mant­let was added in model D.

Panzer IV model D in France 1940 with the ex­ter­nal gun mant­let and periscope. source

Note the front half of the tur­ret top is smooth. There is a pro­tru­sion to the front left of the cupola (I be­lieve it’s a periscope sight) and an­other cir­cu­lar open­ing to the front right. Finally, note the large ven­ti­la­tion hatch just in front of the cupola.

Model E would elim­i­nate the ven­ti­la­tion hatch and re­place it with a fan. The periscope was re­placed with a hatch for sig­nal flags.

Panzer IV model D en­tered mass pro­duc­tion in October 1939 which means it would be too late for Poland, but could have seen ser­vice in France, Norway, or the Soviet Union.

As for the sol­dier…

The ri­fle has a turned down bolt han­dle, a bay­o­net lug (missing from late ri­fles), a dis­tinc­tive dis­as­sem­bly disc on the side of the stock (also miss­ing from late ri­fles), no front site hood (indicative of an early ri­fle), and you can just about make out ex­tra de­tail in the nose cap (also early). This is likely an early Karabiner 98k which is miss­ing its clean­ing rod. See Forgotten Weapons: Evolution of the Karabiner 98k, From Prewar to Kriegsmodell.

ConeOfArc posted a video The Search for Panzer of the Lake.

He broke down what he could iden­tify about the sol­der, prob­a­bly German.

For the tank he con­firms it’s a Panzer IV D us­ing sim­i­lar cri­te­ria I used and he found two ad­di­tional pho­tos of what ap­pear to be the same tank claim­ing to be from the Western front in 1940.

He then found a Russian source claim­ing it was found in Romania at the on­set of Barbarossa in 1941.

Unfortunately that’s all for now. ConeOfArc has put a bounty of $100 US for de­fin­i­tive proof of the tank’s lo­ca­tion. More de­tail can be had on ConeOfArc’s Discord.