Think in Context: Google I/O 2024 Keynote With Google CEO Sundar Pichai

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tl;dr

  • To cater to both individual and enterprise users, Google’s product lineup is more fragmented and scattered compared to Amazon, AWS. This isn’t necessarily a bad thing, but it’s not necessarily good either. Synchronization between products could be more challenging.
  • Google’s models Gemini and Gemma aim to handle long-form context, multimodal inputs, and information across file formats. However, maintaining technical leadership (facing developers, partners, and the ecosystem), multimodal outputs (facing customer needs), and controlling costs (facing investors) will be urgent priorities for Google as it integrates Gemini into hundreds of Google products and features.
  • Amidst this AI wave and technological iterations, the part that left the deepest impression on me from the entire keynote was this quote from DONALD GLOVER: “Everybody's going to become a director and everybody should be a director. Because at the heart of all of this is just storytelling. The closer we are to being able to tell each other our stories, the more we will understand each other.
  • While we’re at it, can’t Google leverage Gemini’s long context advantage to allow Google Translate to properly translate “LLM” as “large language model” instead of “Master of Laws” in the appropriate context?

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Think in Context: NVIDIA GTC 2024 Keynote with NVIDIA CEO Jensen Huang

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tl;dr

At GTC 2024 representing over $100 trillion in global industries, the focus shifted from reducing computing costs to exponentially increasing computing scales. This paradigm shift is dubbed “generation” rather than “inference,” signaling a move away from traditional data retrieval methods towards generating intelligent outputs. The discussion highlighted the ongoing industrial revolution in artificial intelligence, where even complex entities like proteins, genes, and brain waves are being digitized and understood through AI, leading to the creation of their digital twins.

The keynote stressed the transformation of AI applications, citing the AI Foundry’s three main components: NIM, NeMo Microservices, and DGX Cloud. These tools underscore a new era where both structured and unstructured data is converted into a dynamic AI database. This database not only stores information but interacts intelligently with users, marking a significant evolution from traditional semantic encoding to a world where meaning is embedded in digitally generated scenes.

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PHP Performance Benchmark (2024Q1) - PHP8/PHP7 Debian/Alpine nginx-php-fpm

Post Title Image (Image source: Photo by Jason Dent on Unsplash)

This PHP container was developed, adjusted, and maintained together with a friend and colleague. The original design purpose was to combine php-fpm with nginx, creating a simplified environment that facilitates the operation of Laravel in cloud-native environments, AWS Fargate, Amazon ECS, etc. We use it as a base for teaching and implementing various projects, comparative testing, including comparisons of x86/ARM computing architectures, and more.

With the update and release of new PHP versions, we plan to share the performance tests comparisons we’ve conducted every quarter (if not forgotten) with fellow PHP enthusiasts.

Preview

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Simple Guide to Using Anthropic Claude 3 With Amazon Bedrock

Post Title Image (Caption: A sonnet situated on a bedrock connecting knowledge graphs. Image source: generated by DALL-E.)

On 2024-03-04, Anthropic released the Anthropic Claude 3 model family. On the same day, Amazon also announced Amazon Bedrock adds Claude 3 Anthropic AI models.

This article will provide a simple guide to getting started with Claude 3 on Amazon Bedrock and exploring its capabilities. After playing around with it, you might feel more inclined to integrate these LLM models into your workflow to some extent.

Quick glossary:

  • Anthropic: A company focused on AI safety and research.
  • Anthropic Claude 3: A family of models including several different sizes suitable for various application scenarios.
  • Amazon Bedrock: An AI one-stop shopping portal provided by Amazon that offers the simplest way to start using, building, and scaling generative AI applications, incorporating responsible AI.

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Read With Me: How to Do Great Work

Post Title Image (Caption: First attempt at creating a thumbnail, likely only in 720P resolution, let’s go with it for now XDD. Image source: Ernest.)

The originally planned holiday trip was canceled at the last minute, so why not get up early and do some reading? I had been holding onto Paul Graham’s long essay How to Do Great Work. Coincidentally, I came across a high-quality Chinese translation 【如何做出偉大的成就】 shared by Michael Chou, the founder and chief editor of Daodu.tech (科技島讀). So, my reading for the morning was decided on this piece.

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AWS Learning Path and Strategy (2023)

cat-learning-path (Illustration: A cat is required for happy learning, right? Let’s cats lead the way XDD Image source: Photo by hp koch on Unsplash。)

Volunteers of AWSUG Taiwan have always enthusiastically discussed how to lead newbies to get started with AWS more smoothly. Recently I organized all the AWS learning resources that you often discuss and some (unpopular?!) learning ideas that I found into an single article to share with you.

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When Meteor-Grade AI Comes Knocking, Do We Still Need to Learn AWS? 👉 A Traveler's Perspective on a Decade of Decomposition and Integration (AWS Community Day Taiwan 2023)

Post Title Image (Illustration: Slide title cover. Image source: Ernest.)

At the AWS Community Day Taiwan 2023 conference organized by the community, I aimed to address two key aspects. Firstly, to break down the complex and vast amount of AWS product information for attendees who might be overwhelmed by the information or struggling to find direction. Secondly, I adapted the content from a 10-minute presentation at the 4/19 Generative AI Meetup to a 20-minute version. Through examples, we introduced the importance of Frameworks and Foundations, and further presented five tools for organizing knowledge. These tools were integrated into the Ernest PKM IIDEE or Amazon Working Backwards frameworks. Lastly, I took this opportunity to record the session.

I extend my gratitude to Amy Lee, the organizer of AWS Community Day Taiwan 2023, and to Eric and Wyne from Track A for their invitations. I also thank the enthusiastic volunteers and sponsors at the event, which made the second edition of AWS Community Day Taiwan vibrant and energetic. It truly serves as a blessing for AWS enthusiasts and developers alike.

For more details about the expansion of the personal knowledge system, you can read more in-depth in my article 👉 Ernest PKM. In addition to organizing human thoughts, this version includes integrating human-computer collaboration and breaking down historical context.

The significance of historical context is emphasized, echoing the words of Werner Vogels (Amazon.com CTO) at AWS re:Invent 2020:


Technology always moves forwards, but sometimes it’s good to look back, to look at where we came from, to understand our foundation.” – Werner Vogels, Amazon.com CTO at AWS re:Invent 2020

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Decomposition & Comparison: Why sometimes AWS CLI create-invalidation cannot clear Amazon CloudFront cache

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Introduction

Since moving my blog from GitHub Pages to Amazon S3 + Amazon CloudFront, the deployment time and webpage loading time have been greatly reduced.

Even for long articles like Ernest PKM (Personal Knowledge Management) Workflow, the webpage loading time can still achieve DOMContentLoaded < 650 ms and Load < 2.5 s. The deployment time has been significantly reduced from an average of 10-13 minutes on GitHub Pages build to less than 1 minute when there are no image changes.

However, this led to another issue of managing and deciding the CDN cache expiration period.

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Ernest PKM Personal Knowledge System Workflow (2023.25)

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✳️ Introduction

(Initial version on 2023-02-16)

Since childhood, probably elementary school, I’ve been fascinated by notebooks, enjoying recording numbers, temperatures, times, the number of pigeons on the neighboring building outside the window, and how long it takes for them to fly around and return to their pigeon house, etc.

As I grew older, I’ve always regarded notebooks as tools for recording, memorizing, and quick review. However, I felt that they didn’t match my workflow, whether at work or at home. In recent years, I’ve been better at integrating them into my workflow and documenting my current Personal Knowledge Management (PKM) process. This workflow is derived from the various shares of many people who are smarter and more focused on PKM, Smart Notes, and other areas than me.

This workflow may not be suitable for everyone, but I hope that by sharing these ideas, we can spark conversations and discussions that help us, and even our next generation, reduce the time spent exploring and improve learning or work efficiency, ultimately contributing to society or humanity.

AI, Machine Learning, ChatGPT, Google Bard, Amazon Titan, Auto-GPT, and other models and artificial intelligence tools can handle some tasks for us, but they also operate following a certain process. If we can master the idea of process design, I believe we can still make a difference in society and organizations. Let’s encourage each other.


(Updated to 2023.25 version on 2023-04-19)

Originally, I thought the Ernest PKM series of articles would be updated once a year, but in just a quarter of a year (0.25 year), various AI thoughts and products have descended like meteorites, prompting a forced industry upgrade.

Since the GPT version numbers have evolved from GPT-1, GPT-2, GPT-3, GPT-3.5, to GPT-4, Ernest PKM has also undergone a minor upgrade, integrating both human brain and AI (MLOps) workflows, resulting in the Ernest PKM 2023.25 version. I chose to publish it on 4/19 Generative AI Meetup to share and interact with old friends and new acquaintances whom I haven’t seen for a long time.

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Heptabase Quick Capture mobile app

Post Title Image (Photo by Ash Edmonds on Unsplash)

Today, while I am sorting out the draft of the newly released Ernest’s Personal Knowledge System Workflow (2023), I found some exciting news. Alan announced on the Discord channel that Heptabase is entering the mobile space for the first time, launching the Heptabase Quick Capture mobile app. It is released on both Google Play and Apple TestFlight.

You can quickly capture ideas directly on your phone and record them in the Heptabase Quick Capture mobile app, and then it will be sent to the Heptabase Card Library. For more details, please refer to the “2️⃣ Inbox” section of Ernest’s Personal Knowledge System Workflow (2023).

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