Your Guide To Using Amazon’s Sidewalk Network For The Internet Of Things

As the Internet of Things became a mainstream reality, it raised an interesting point about connectivity. We quickly learned it wasn’t ideal to have every light bulb, toaster, and kettle buzzing away on our main WiFi networks. Nor was it practical to sign up for a cellular data plan for every tracker tag or remote sensor we wanted to use.

To solve this issue, various tech companies have developed their own low-power mesh networking solutions. Amazon’s Sidewalk network is one of the widest spread in the US. Now, it’s opening it up for wider use beyond its own products, and you can get in on the action.

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The Modern WWW, Or: Where Do We Want To Go From Here?

From the early days of ARPANET until the dawn of the World Wide Web (WWW), the internet was primarily the domain of researchers, teachers and students, with hobbyists running their own BBS servers you could dial into, yet not connected to the internet. Pitched in 1989 by Tim Berners-Lee while working at CERN, the WWW was intended as an information management system that’d provide standardized access to information using HTTP as the transfer protocol and HTML and later CSS to create formatted documents inspired by the SGML standard. Even better, it allowed for WWW forums and personal websites to begin to pop up, enabling the eternal joy of web rings, animated GIFs and forums on any conceivable topic.

During the early 90s, as the newly opened WWW began to gain traction with the public, the Mosaic browser formed the backbone of the WWW browsers (‘web browsers’) of the time, including Internet Explorer – which licensed the Mosaic code – and the Mosaic-based Netscape Navigator. With the WWW standards set by the – Berners-Lee-founded – World Wide Web Consortium (W3C), the stage appeared to be set for an open and fair playing field for all. What we got instead was the brawl referred to as the ‘browser wars‘, which – although changed – continues to this day.

Today it isn’t Microsoft’s Internet Explorer that’s ruling the WWW while setting the course for new web standards, but instead we have Google’s Chrome browser partying like it’s the early 2000s and it’s wearing an IE mask. With former competitors like Opera and Microsoft having switched to the Chromium browser engine that underlies Chrome, what does this tell us about the chances for alternative browsers and the future of the WWW?

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Peering Down Into Talking Ant Hill

Watching an anthill brings an air of fascination. Thousands of ants are moving about and communicating with other ants as they work towards a goal as a collective whole. For us humans, we project a complex inner world for each of these tiny creatures to drive the narrative. But what if we could peer down into a miniature world and the ants spoke English? (PDF whitepaper)

Researchers at the University of Stanford and Google Research have released a paper about simulating human behavior using multiple Large Language Models (LMM). The simulation has a few dozen agents that can move across the small town, do errands, and communicate with each other. Each agent has a short description to help provide context to the LLM. In addition, they have memories of objects, other agents, and observations that they can retrieve, which allows them to create a plan for their day. The memory is a time-stamped text stream that the agent reflects on, deciding what is important. Additionally, the LLM can replan and figure out what it wants to do.

The question is, does the simulation seem life-like? One fascinating example is the paper’s authors created one agent (Isabella) intending to have a Valentine’s Day party. No other information is included. But several agents arrive at the character’s house later in the day to party. Isabella invited friends, and those agents asked some people.

A demo using recorded data from an earlier demo is web-accessible. However, it doesn’t showcase the powers that a user can exert on the world when running live. Thoughts and suggestions can be issued to an agent to steer their actions. However, you can pause the simulation to view the conversations between agents. Overall, it is incredible how life-like the simulation can be. The language of the conversation is quite formal, and running the simulation burns significant amounts of computing power. Perhaps there can be a subconscious where certain behaviors or observations can be coded in the agent instead of querying the LLM for every little thing (which sort of sounds like what people do).

There’s been an exciting trend of combining LLMs with a form of backing store, like combining Wolfram Alpha with chatGPT. Thanks [Abe] for sending this one in!

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Hackaday Links: April 16, 2023

The dystopian future you’ve been expecting is here now, at least if you live in New York City, which unveiled a trio of technology solutions to the city’s crime woes this week. Surprisingly, the least terrifying one is “DigiDog,” which seems to be more or less an off-the-shelf Spot robot from Boston Dynamics. DigiDog’s job is to de-escalate hostage negotiation situations, and unarmed though it may be, we suspect that the mission will fail spectacularly if either the hostage or hostage-taker has seen Black Mirror. Also likely to terrify the public is the totally-not-a-Dalek-looking K5 Autonomous Security Robot, which is apparently already wandering around Times Square using AI and other buzzwords to snitch on people. And finally, there’s StarChase, which is based on an AR-15 lower receiver and shoots GPS trackers that stick to cars so they can be tracked remotely. We’re not sure about that last one either; besides the fact that it looks like a grenade launcher, the GPS tracker isn’t exactly covert. Plus it’s only attached with adhesive, so it seems easy enough to pop it off the target vehicle and throw it in a sewer, or even attach it to another car.

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Tired Of Web Scraping? Make The AI Do It

[James Turk] has a novel approach to the problem of scraping web content in a structured way without needing to write the kind of page-specific code web scrapers usually have to deal with. How? Just enlist the help of a natural language AI. Scrapeghost relies on OpenAI’s GPT API to parse a web page’s content, pull out and classify any salient bits, and format it in a useful way.

What makes Scrapeghost different is how data gets organized. For example, when instantiating scrapeghost one defines the data one wishes to extract. For example:

from scrapeghost import SchemaScraper
scrape_legislators = SchemaScraper(
schema={
"name": "string",
"url": "url",
"district": "string",
"party": "string",
"photo_url": "url",
"offices": [{"name": "string", "address": "string", "phone": "string"}],
}
)

The kicker is that this format is entirely up to you! The GPT models are very, very good at processing natural language, and scrapeghost uses GPT to process the scraped data and find (using the example above) whatever looks like a name, district, party, photo, and office address and format it exactly as requested.

It’s an experimental tool and you’ll need an API key from OpenAI to use it, but it has useful features and is certainly a novel approach. There’s a tutorial and even a command-line interface, so check it out.

Rock, paper, scissors game that uses servos to choose one at random for the computer.

Forget ChatGPT And Play Rock-Paper-Scissors With Yourself Instead

This isn’t like the cool AI everyone’s getting caught up with these days, but we’re sure it will make a fun party gimmick nonetheless.

The premise of [CrazyScience]’s game is really simple, with three servos connected to labels that display rock, paper, and scissors, respectively. The game code is written to pick a label to display at random. Furthermore, an ultrasonic distance sensor detects when the player has moved their hand close to the game, indicating the player has chosen a hand and is challenging the game. The result of the game is decided by the player, so we imagine you could pretend you never lost and no one would know.

It would be cool to see the game support multiple players, keep score, or make sure you can never win. And you’ll probably want to add the randomSeed function in the code too. But that seems like a version two problem.

The only thing left to do is add some AI since that’s all we’re doing nowadays. But maybe you’re the type to enjoy the simple 8-bit pleasures instead. If you ask us though, we’d rather play with friends.

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Hackaday Does Berlin

If you’re wondering why there was no newsletter last weekend, it was because we had our hands full with Hackaday Berlin. But boy, was it worth it! Besides being the launch party for the tenth annual Hackaday Prize, it was the first Hackaday gathering in Europe for four years, and it was awesome to see a bunch of familiar faces and meet many more new ones.

In a world that’s so interconnected, you might think that social media can take care of it all for you. And to some extent that’s true! If I could count the number of times I heard “I follow you on Twitter/Mastodon” over the course of the event!

But then there were tons of other meetings. People who are all interested in building and designing analog synthesizers, even some who live in the same urban megalopolis, meeting each other and talking about modules and designs. People who love flip dots. On the spot collaborations of people writing video drivers and people making huge LED walls. And somehow there’s still room for this to happen, even though the algorithms should have probably hooked these folks up by now.

From the perspective of hosting the conference, I get the most satisfaction from seeing these chance meetings and the general atmosphere of people learning not only new things, but new people. This cross-fertilization of friendships and project collaborations is what keeps our community vital, and especially coming out of the Pandemic Years, it’s absolutely necessary. I came away with a long list of new plans, and I’m sure everyone else did too. And for some reason, social media just isn’t a substitute. Take that, TwitFace!