Dale Markowitz dalequark

Big Context Windows are a Bigger Deal Than You Think

This blog post was generated by Gemini 1.5 in the style of DaleOnAI.com

Remember when we used to marvel at LLMs that could handle a few thousand tokens of context? Well, hold onto your hats, folks, because Google just dropped Gemini 1.5, a multimodal LLM with a 1 million token context window. That's not just a bigger window, it's a whole new way of looking at how we interact with LLMs.

Sure, the ability to dump massive documents, movies, and audio into a single prompt is cool. Imagine asking an LLM to compare two movies after consuming both in their entirety, or to summarize a dense legal document. But the real magic of Gemini 1.5 isn't just the size of the window, it's the near-perfect recall and improved reasoning that comes with it.

Jeff Dean himself pointed out the significance of this breakthrough on Twitter, referencing DeepMind's "needle in a haystack" tests. These tests showed that Gemini 1.5 can not only access millions of tokens, b

	function huntForPets(monitoredItem, detectionArray, target) {
	// naughtyAnimals is an array that keeps track of each animal are in frame
	var naughtyAnimals = [];

	// Loop through all of the objects recognized by the API
	for (let i = 0; i < detectionArray.length; i++) {
	// If we found one of the objects we were looking for...
	if (detectionArray[i].class === target && detectionArray[i].score > MIN_DETECTION_CONFIDENCE) {
	// Draw a bounding box on screen
	renderFoundObject(detectionArray[i]);

	class BBox {
	constructor(bbox) {
	let x = bbox[0];
	let y = bbox[1];
	this.width = bbox[2];
	this.height = bbox[3];
	this.midX = x + this.width / 2;
	this.midY = y + this.height / 2;
	}

	<!-- Load TensorFlow.js. This is required to use coco-ssd model. -->
	<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"> </script>

	<!-- Load the coco-ssd model. -->
	<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/coco-ssd"> </script>

	<script>
	// Grab DOM reference to video element.
	const video = document.getElementById('webcamVideo');

	[
	{
	"transcript": "Software developers. We're not known for our Rock and style. Are we or are we today? I'll show you how I use ml to make new trendier taking inspiration from influencers. I'm going to build an app that analyzes my closet and pictures of fashionable influencers and then makes me outfit recommendations. If I'm missing an important piece will also recommend me products to buy let me show you how",
	"words": [
	{
	"word": "Software",
	"start_time": 0.2,
	"end_time": 0.6,
	"speaker_tag": 0
	},

	/**
	* Copyright 2020 Google LLC
	*
	* Licensed under the Apache License, Version 2.0 (the "License");
	* you may not use this file except in compliance with the License.
	* You may obtain a copy of the License at
	*
	* http://www.apache.org/licenses/LICENSE-2.0
	*
	* Unless required by applicable law or agreed to in writing, software

	def canAddItem(existingArray, newType):
	bottoms = {"pants", "skirt", "shorts", "dress"}
	newType = newType.lower()
	if newType in existingArray:
	return False
	if newType == "shoe":
	return True
	if newType in bottoms and len(bottoms.intersection(existingArray)):
	return False
	if newType == "top" and "dress" in existingArray:

	sudo apt-get update && sudo apt-get install -y git python3-dev python3-pygame python3-venv libatlas-base-dev libasound2-dev python3-pyaudio

	sudo cp /usr/share/alsa/alsa.conf /usr/share/alsa/alsa.conf.orig

	echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] https://packages.cloud.google.com/apt cloud-sdk main" \| sudo tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
	sudo apt-get install apt-transport-https ca-certificates gnupg
	curl https://packages.cloud.google.com/apt/doc/apt-key.gpg \| sudo apt-key --keyring /usr/share/keyrings/cloud.google.gpg add -
	sudo apt-get update && sudo apt-get install google-cloud-sdk