Robin Lord
@RobinLord8
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Head of Innovation @airadigital. Digital marketer and strategist. All views regurgitated versions of what my upbringing tells me to think.
Joined October 2012
@dom_woodman @noahlearner @soulwire If you're interested please do check out the game, it has been a really fun project for me, it's totally free and I hope you enjoy it, can't wait to hear what you think -) https://t.co/a65a2O8JgR
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Want an easier way to handle GA4 BigQuery? We're launching Pipeline! Enterprise level GA4 data in 15 minutes, with no SQL or data engineering. Session level dimensions, multi touch attribution, Looker Studio connector. All ready to go.
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Really excited to hear what you all think of it! Go here to check out the game: https://t.co/AgHhyoXLLP You'll need to be on something like a laptop to play, purely because this kind of thing would be too much of a pain to do on a small touch screen 😊
divided-we-fall.therobinlord.com
Divided We Fall is a game that helps you challenge yourself and improve your HTML and CSS skills
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If you're brand new to HTML and CSS - don't worry! There's a bunch of guidance, links to learn from, and the option to just take an answer if all else fails. If you're a seasoned pro - you can jump in and test your HTML skills in a brand new way.
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Excited to share a new game I've been working on! In Divided We Fall you control an adorable bouncy cube as it takes on a perilous dungeon. As you progress - your challenge is to create the levels for you to bounce across, using HTML & CSS skills you pick up
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Great post for SEO's looking for an introduction to LLMs through the language of how SEO's look at information gathering, retrieval, etc by @RobinLord8. https://t.co/6WdQK4FFlG
moz.com
Whether you’re a user or a marketer, Robin will explain to you what you should absolutely know about Large Language Models.
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It has been SO useful to get an idea of how historic GA4 data might have looked, before it was live on site has been wildly useful. Here Dave is sharing a way to do it, free! Check it out!
📊 New Post - How to backdate your GA4 analytics history before having GA4 tracking set up 📊 https://t.co/qbiALxvBol
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Jason has long been my go-to source for breaking down Google and Meta legal developments, particularly when it comes to things like tracking, looks like he'll be my go-to for OpenAI and LLM copyright law developments too!
ok, I've now read the full NYT complaint filed this morning vs OpenAI and Microsoft. I'm impressed - it's future-focused around fair value for work vital to democracy. It also contains 220k pages of exhibits although the pages of Ex J stood out to me. more on that in a minute. /1
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I don't really have a point to wrap this up, other than - I'm not disagreeing with the underlying points being made 😊
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A good friend of mine works for a large Airbnb competitor. He told me that their biggest hiring challenge is SEOs often struggle with having *so* much free reign to make changes because so many are used to 90% of their time being spent on politics.
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But the solution might be to find a new agency where you can get things done. You'll probably find it quite informative to think about whether that scares you.
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But if you feel like your SEO client isn't set up for SEO - that doesn't *necessarily* make you a bad or negligent person. It's not an excuse to check out and blame everything on sales - you have the same responsibility to go in each day and focus on affecting change.
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I think this sentiment is important *but* it's worth bearing in mind that many consultants in agencies don't have say over what clients are sold and assigned to them and certainly can't fire them. Totally agree with what Tory says here in terms of fighting to educate
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It's becoming a more and more common solution to inject recent data into short term memory (context window) as a way to fill in gaps in Large Language Model knowledge and paper over hallucination. Nice approach here, using Wikipedia as a database
8/n That was the 4th reveal yesterday. The 5th reveal was work by Stanford to develop an architecture that leads to more factual LLMs. WikiChat uses Wikipedia and the following 7-stage pipeline to makes sure its responses are factual. https://t.co/0nVYYxJSL0
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Many are liking this because it casts their poor impulse control and hierarchy blindness as a social good rather than just a problem. Well, that's why I liked it anyway.
Every company needs 2-3 senior+ engineers who have fuck you money or just have 0 fear of getting fired. Then when the architect or tech fellow or whoever unveil their new plan, those engineers unmute to say wtf is this, we're not moving everything into Lambda, are you high???
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Interesting summary of the drawbacks of building your own GPT-esque bot. It brushes over the fact that these things aren't all-or-nothing (you can augment GPT with your own data in a vector database) but even "just" RAG is a big data pipelining problem. https://t.co/9Hoa0I8eur
medium.com
From hallucinations to lack of citations and sources. To data ingestion issues to query relevancy shortfalls. From MLOps to mounting…
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Another amazing example of "Everything is selection".* This experiment is really neat, so let's go through it. Facebook users are exposed to more like-minded than cross-cutting news sources. In yellow, you see how this looks for people who were enrolled in this study and in
It would appear people are in echo chambers because they are polarized, not that they are polarized because they are in echo chambers.
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(Shout out to @dom_woodman for originally encouraging me to make summary tabs for sheets years ago. When I've done it I've often been glad, and when I've not bothered I've often regretted it!)
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As a final note on data safety - if you're thinking of trying something like this, it's really worth doing it through the API. While there are ways of turning off training in ChatGPT - OpenAI guarantee that API inputs and outputs won't be used to train models
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Tab summariser will give our team - A summary of the kinds of data in each tab - Insights based on patterns in the data - Details of potential errors, or things that could be misleading about the data All that will help us to be clearer and more accurate with data we share
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We've been thinking for a while that it would be valuable to auto-generate some summary descriptions of sheets, to give our team a starting point for making sheets clearer. OpenAI's new model can handle thousands of rows of data so it seemed like the perfect excuse to try it!
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