The Rise of the LLMs - How I Learned to Stop Worrying & Love the GPT!

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taozen

LLM, ChatGPT, AI. A take on the new wave! After the PC, the internet, mobile and the cloud, the new wave is here: AI

The rise of LLMs
or: How I Learned to Stop Worrying and
Love the GPT
(ChatGPT did not write this presentation. Or did it?)
Feb 2023 – Laurent Lathieyre
*draft 0.2

the
ubiquitous
natural language
prompt
> text
💬 voice
will be part of
any/all
human-machine
interface

after
pc
internet
mobile
cloud
the new wave is
here
> ai <
…

…
and probably in
its most most
disruptive form
factor:
AI as a platform

coming in the
near future:
multi-modal
models (text,
image, video,
etc.)
continuous
learning (i.e.
not stuck in
time)

coming in a not
so distant
future:
Artificial
General
Intelligence
(AGI)

There will be
only a few LLMs
providers
aka “resistance
is futile ; don’t
try to train your
own LLM”
OpenAI ; Google ; Microsoft ; Facebook ; Amazon ; IBM ; Alibaba ; Tencent ; Baidu ;
Intel ; Nvidia

there is room in
the value chain
for
category/vertical
model fine tuners
on top of LLMs

importance of 1st
and 2nd party
data
Access to data will be key to success in the field of AI, and businesses will need to
consider data privacy and security as well as how language models can be used to
improve existing products and services, create new products and services, automate
tasks, and provide personalized experiences for customers.

legal ops
applications
-co-drafting
-generation
-documents
semantic search
-translation
-general access
to law knowledge
and jurisprudence

the way forward:
embrace the unknown,
harvest chaos to create
opportunities and drive
innovation
(to be continued)
Dall-e: draw a team of pioneers, some are holding a spear, they jump into a portal to
another dimension, digital art

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The lecture titled "Automating AppSec" delves into the critical challenges associated with manual application security (AppSec) processes and outlines strategic approaches for incorporating automation to enhance efficiency, accuracy, and scalability. The lecture is structured to highlight the inherent difficulties in traditional AppSec practices, emphasizing the labor-intensive triage of issues, the complexity of identifying responsible owners for security flaws, and the challenges of implementing security checks within CI/CD pipelines. Furthermore, it provides actionable insights on automating these processes to not only mitigate these pains but also to enable a more proactive and scalable security posture within development cycles. The Pains of Manual AppSec: This section will explore the time-consuming and error-prone nature of manually triaging security issues, including the difficulty of prioritizing vulnerabilities based on their actual risk to the organization. It will also discuss the challenges in determining ownership for remediation tasks, a process often complicated by cross-functional teams and microservices architectures. Additionally, the inefficiencies of manual checks within CI/CD gates will be examined, highlighting how they can delay deployments and introduce security risks. Automating CI/CD Gates: Here, the focus shifts to the automation of security within the CI/CD pipelines. The lecture will cover methods to seamlessly integrate security tools that automatically scan for vulnerabilities as part of the build process, thereby ensuring that security is a core component of the development lifecycle. Strategies for configuring automated gates that can block or flag builds based on the severity of detected issues will be discussed, ensuring that only secure code progresses through the pipeline. Triaging Issues with Automation: This segment addresses how automation can be leveraged to intelligently triage and prioritize security issues. It will cover technologies and methodologies for automatically assessing the context and potential impact of vulnerabilities, facilitating quicker and more accurate decision-making. The use of automated alerting and reporting mechanisms to ensure the right stakeholders are informed in a timely manner will also be discussed. Identifying Ownership Automatically: Automating the process of identifying who owns the responsibility for fixing specific security issues is critical for efficient remediation. This part of the lecture will explore tools and practices for mapping vulnerabilities to code owners, leveraging version control and project management tools. Three Tips to Scale the Shift Left Program: Finally, the lecture will offer three practical tips for organizations looking to scale their Shift Left security programs. These will include recommendations on fostering a security culture within development teams, employing DevSecOps principles to integrate security throughout the development

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This brochure gives introduction of MYIR Electronics company and MYIR's products and services. MYIR Electronics Limited (MYIR for short), established in 2011, is a global provider of embedded System-On-Modules (SOMs) and comprehensive solutions based on various architectures such as ARM, FPGA, RISC-V, and AI. We cater to customers' needs for large-scale production, offering customized design, industry-specific application solutions, and one-stop OEM services. MYIR, recognized as a national high-tech enterprise, is also listed among the "Specialized and Special new" Enterprises in Shenzhen, China. Our core belief is that "Our success stems from our customers' success" and embraces the philosophy of "Make Your Idea Real, then My Idea Realizing!"

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If you’ve ever had to analyze a map or GPS data, chances are you’ve encountered and even worked with coordinate systems. As historical data continually updates through GPS, understanding coordinate systems is increasingly crucial. However, not everyone knows why they exist or how to effectively use them for data-driven insights. During this webinar, you’ll learn exactly what coordinate systems are and how you can use FME to maintain and transform your data’s coordinate systems in an easy-to-digest way, accurately representing the geographical space that it exists within. During this webinar, you will have the chance to: - Enhance Your Understanding: Gain a clear overview of what coordinate systems are and their value - Learn Practical Applications: Why we need datams and projections, plus units between coordinate systems - Maximize with FME: Understand how FME handles coordinate systems, including a brief summary of the 3 main reprojectors - Custom Coordinate Systems: Learn how to work with FME and coordinate systems beyond what is natively supported - Look Ahead: Gain insights into where FME is headed with coordinate systems in the future Don’t miss the opportunity to improve the value you receive from your coordinate system data, ultimately allowing you to streamline your data analysis and maximize your time. See you there!

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Mobile performance metrics often take inspiration from the backend world and measure resource usage (CPU usage, memory usage, etc) and workload durations (how long a piece of code takes to run). However, mobile apps are used by humans and the app performance directly impacts their experience, so we should primarily track user-centric mobile performance metrics. Following the lead of tech giants, the mobile industry at large is now adopting the tracking of app launch time and smoothness (jank during motion). At Square, our customers spend most of their time in the app long after it's launched, and they don't scroll much, so app launch time and smoothness aren't critical metrics. What should we track instead? This talk will introduce you to Interaction Latency, a user-centric mobile performance metric inspired from the Web Vital metric Interaction to Next Paint"" (web.dev/inp). We'll go over why apps need to track this, how to properly implement its tracking (it's tricky!), how to aggregate this metric and what thresholds you should target.

HTTP Adaptive Streaming – Quo Vadis (2024)

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Video traffic on the Internet is constantly growing; networked multimedia applications consume a predominant share of the available Internet bandwidth. A major technical breakthrough and enabler in multimedia systems research and of industrial networked multimedia services certainly was the HTTP Adaptive Streaming (HAS) technique. This resulted in the standardization of MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) which, together with HTTP Live Streaming (HLS), is widely used for multimedia delivery in today’s networks. Existing challenges in multimedia systems research deal with the trade-off between (i) the ever-increasing content complexity, (ii) various requirements with respect to time (most importantly, latency), and (iii) quality of experience (QoE). Optimizing towards one aspect usually negatively impacts at least one of the other two aspects if not both. This situation sets the stage for our research work in the ATHENA Christian Doppler (CD) Laboratory (Adaptive Streaming over HTTP and Emerging Networked Multimedia Services; https://athena.itec.aau.at/), jointly funded by public sources and industry. In this talk, we will present selected novel approaches and research results of the first year of the ATHENA CD Lab’s operation. We will highlight HAS-related research on (i) multimedia content provisioning (machine learning for video encoding); (ii) multimedia content delivery (support of edge processing and virtualized network functions for video networking); (iii) multimedia content consumption and end-to-end aspects (player-triggered segment retransmissions to improve video playout quality); and (iv) novel QoE investigations (adaptive point cloud streaming). We will also put the work into the context of international multimedia systems research.

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1. The rise of LLMs or: How I Learned to Stop Worrying and Love the GPT (ChatGPT did not write this presentation. Or did it?) Feb 2023 – Laurent Lathieyre *draft 0.2

2. 1M users 5-day after launch

3. viral growth fastest reach to 1M users

4. the ubiquitous natural language prompt > text 💬 voice will be part of any/all human-machine interface

5. after pc internet mobile cloud the new wave is here > ai < …

6. … and probably in its most most disruptive form factor: AI as a platform

7. coming in the near future: multi-modal models (text, image, video, etc.) continuous learning (i.e. not stuck in time)

8. coming in a not so distant future: Artificial General Intelligence (AGI)

9. There will be only a few LLMs providers aka “resistance is futile ; don’t try to train your own LLM” OpenAI ; Google ; Microsoft ; Facebook ; Amazon ; IBM ; Alibaba ; Tencent ; Baidu ; Intel ; Nvidia

10. there is room in the value chain for category/vertical model fine tuners on top of LLMs

11. importance of 1st and 2nd party data Access to data will be key to success in the field of AI, and businesses will need to consider data privacy and security as well as how language models can be used to improve existing products and services, create new products and services, automate tasks, and provide personalized experiences for customers.

12. legal ops applications -co-drafting -generation -documents semantic search -translation -general access to law knowledge and jurisprudence

13. the way forward: embrace the unknown, harvest chaos to create opportunities and drive innovation (to be continued) Dall-e: draw a team of pioneers, some are holding a spear, they jump into a portal to another dimension, digital art

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