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In an era where security concerns are paramount, the integration of artificial intelligence (AI) into CCTV cameras has revolutionized surveillance capabilities. One of the most significant advancements is the ability to achieve real-time threat detection, enabling immediate responses to potential security breaches. This blog explores how AI is reshaping surveillance through real-time threat detection and the implications of this technology.
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In this blog, we embark on a journey into the realm of Server-Side Rendering with NuxtJS, unraveling its capabilities and demonstrating how it can be a catalyst for an unparalleled web experience.
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Foundation models are machine learning models which are easily capable of performing variable tasks on large and huge datasets. FMs have managed to get a lot of attention due to this feature of handling large datasets. It can do text generation, video editing to protein folding and robotics. In case we believe that FMs can help the hospitals and patients in any way, we need to perform some important evaluations, tests to test these assumptions. In this review, we take a walk through Fms and their evaluation regimes assumed clinical value. To clarify on this topic, we reviewed no less than 80 clinical FMs built from the EMR data. We added all the models trained on structured and unstructured data. We are referring to this combination of structured and unstructured EMR data or clinical data.
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Azure Native Qumulo scales elastically for common High Performance Compute (HPC) workloads based on application requirements for: Financial Services, Automotive, Genomics / Life Sciences, Media and Entertainment, Energy, Oil and Gas, etc. Performance can be dialed UP (and back down) much higher than the examples shown here. These slides offer a glimpse into ANQ's HPC capabilities, although at a smaller scale. We invite YOU to do your own testing (with a free ANQ trial) and work with us to test your HPC workloads in Azure.
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In the realm of real-time applications, Large Language Models (LLMs) have long dominated language-centric tasks, while tools like OpenCV have excelled in the visual domain. However, the future (maybe) lies in the fusion of LLMs and deep learning, giving birth to the revolutionary concept of Large Action Models (LAMs). Imagine a world where AI not only comprehends language but mimics human actions on technology interfaces. For example, the Rabbit r1 device presented at CES 2024, driven by an AI operating system and LAM, brings this vision to life. It executes complex commands, leveraging GUIs with unprecedented ease. In this presentation, join me on a journey as a software engineer tinkering with WebRTC, Janus, and LLM/LAMs. Together, we’ll evaluate the current state of these AI technologies, unraveling the potential they hold for shaping the future of real-time applications.
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Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Dyposits Hotsec
1.
How Can We
Evolve Cyber Physical Security Policies to Automatically Manage Changing Threats? Joseph Hallett
2.
How Can We
Avoid Having Everything Being On Fire? Joseph Hallett
3.
Cyber Physical Systems are
Everywhere
4.
5.
6.
7.
Smart Offices
8.
Smart Water Treatment Plants
9.
Smart Power Generation
10.
Smart Factories
11.
Autonomous Vehicles IOT
12.
13.
14.
15.
❓
16.
❓
17.
18.
❓
19.
💸 💸 💸
20.
21.
❓
22.
23.
24.
25.
26.
HOW DO WE DEFEND AGAINST THIS?
27.
#
28.
#
29.
✅
30.
So what’s the problem?
31.
32.
33.
Handwritten policies do
not scale
34.
The threat landscape isn’t
static
35.
How do we
fix this?
36.
37.
Threats Catalogue of identified threats against
the running of the system
38.
Threats Threats Mitigations Mitigation controls for handling
the threats
39.
Threats Threats Mitigations Policy Language Reconfigure Cyber-Physical System Policy Language selects mitigations based
on threats and reconfigures the CPS
40.
Running in a
MAPE-K loop…
41.
Automation
42.
Automation (should scale)
43.
No ad-hoc reconfiguration
44.
No ad-hoc reconfiguration (should
react faster too)
45.
Why is this controversial?
46.
Dynamic reconfiguration in
a MAPE-K loop is not new
47.
48.
49.
I CAN RECONFIGURE UR
TOWN?
50.
51.
MR. STARK… I DON’T
FEEL SO GOOD
52.
53.
54.
THIS WILL INCREASE THE ATTACK SURFACE
Download now