The Generative AI Revolution: Transforming Industries with Brillio
The realm of artificial intelligence is experiencing a paradigm shift with the emergence of generative AI. Unlike traditional AI models focused on analyzing existing data, generative AI takes a leap forward by creating entirely new content. The generative ai technology unlocks a future brimming with possibilities across diverse industries. Let's read about the transformative power of generative AI in various sectors:
1. Healthcare Industry:
AI for Network Optimization: Generative AI can optimize healthcare networks by predicting patient flow, resource allocation, etc. This translates to streamlined operations, improved efficiency, and potentially reduced wait times.
Generative AI for Life Sciences & Pharma: Imagine accelerating drug discovery by generating new molecule structures with desired properties. Generative AI can analyze vast datasets to identify potential drug candidates, saving valuable time and resources in the pharmaceutical research and development process.
Patient Experience Redefined: Generative AI can personalize patient communication and education. Imagine chatbots that provide tailored guidance based on a patient's medical history or generate realistic simulations for medical training.
Future of AI in Healthcare: Generative AI has the potential to revolutionize disease diagnosis and treatment plans by creating synthetic patient data for anonymized medical research and personalized drug development based on individual genetic profiles.
2. Retail Industry:
Advanced Analytics with Generative AI: Retailers can leverage generative AI to analyze customer behavior and predict future trends. This allows for targeted marketing campaigns, optimized product placement based on customer preferences, and even the generation of personalized product recommendations.
AI Retail Merchandising: Imagine creating a virtual storefront that dynamically adjusts based on customer demographics and real-time buying patterns. Generative AI can optimize product assortments, recommend complementary items, and predict optimal pricing strategies.
Demystifying Customer Experience: Generative AI can analyze customer feedback and social media data to identify emerging trends and potential areas of improvement in the customer journey. This empowers retailers to take proactive steps to enhance customer satisfaction and loyalty.
3. Finance Industry:
Generative AI in Banking: Generative AI can streamline loan application processes by automatically generating personalized loan offers and risk assessments. This reduces processing time and improves customer service efficiency.
4. Technology Industry:
Generative AI for Software Testing: Imagine automating the creation of large-scale test datasets for various software functionalities. Generative AI can expedite the testing process, identify potential vulnerabilities more effectively, and contribute to faster software releases.
Generative AI for Hi-Tech: This technology can accelerate innovation in various high-tech fields by creating novel designs for microchips, materials, or even generating code snippets to enhance existing software functionalities.
Generative AI for Telecom: Generative AI can optimize network performance by predicting potential obstruction and generating data patterns to simulate network traffic scenarios. This allows telecom companies to proactively maintain and improve network efficiency.
5. Generative AI Beyond Industries:
GenAI Powered Search Engine: Imagine a search engine that understands context and intent, generating relevant and personalized results tailored to your specific needs. This eliminates the need to sift through mountains of irrelevant information, enhancing the overall search experience.
Product Engineering with Generative AI: Design teams can leverage generative AI to create new product prototypes, explore innovative design possibilities, and accelerate the product development cycle.
Machine Learning with Generative AI: Generative AI can be used to create synthetic training data for machine learning models, leading to improved accuracy and enhanced efficiency.
Global Data Studio with Generative AI: Imagine generating realistic and anonymized datasets for data analysis purposes. This empowers researchers, businesses, and organizations to unlock insights from data while preserving privacy.
6. Learning & Development with Generative AI:
L&D Shares with Generative AI: This technology can create realistic simulations and personalized training modules tailored to individual learning styles and skill gaps. Generative AI can personalize the learning experience, fostering deeper engagement and knowledge retention.
HFS Generative AI: Generative AI can be used to personalize learning experiences for employees in the human resources and financial services sector. This technology can create tailored training programs for onboarding, compliance training, and skill development.
7. Generative AI for AIOps:
AIOps (Artificial Intelligence for IT Operations) utilizes AI to automate and optimize IT infrastructure management. Generative AI can further enhance this process by predicting potential IT issues before they occur, generating synthetic data for simulating scenarios, and optimizing remediation strategies.
Conclusion:
The potential of generative AI is vast, with its applications continuously expanding across industries. As research and development progress, we can expect even more groundbreaking advancements that will reshape the way we live, work, and interact with technology.
Reference- https://articlescad.com/the-generative-ai-revolution-transforming-industries-with-brillio-231268.html
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https://fnqmarineelectronics.com.au
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since you've been posting your house of h/powers of h stuff again, i'm really curious to know more about your hf fanon, especially human makuro. what's up with that?
Okay damn, long post time:
Full disclaimer a lot of this shit is disjointed and me just redoing a lot of Hero Factory lore with zero regard for much of anything:
Basically, my version of Akiyama Makuro is that he used to be a teen genius who was a sidekick to a legion of galactic superheroes that he idolized. All of these heroes were killed in a battle against Black Phantom and his Legion of Darkness over the planet Quatros and its natural resource Quaza.
The grief-stricken Makuro would eventually research the Quaza and find that it can be imprinted with memories and brain-patterns, but after he figures out a way to synthesize it, Witch Doctor exiles him from Quatros so he and his allies won't desecrate it further. With the Quaza in hand, Makuro begins work on forming Hero Factory and using the Quaza to resurrect his heroes in the form of robotic sentries that will enforce law and order across the galaxy. Unknown to him, Black Phantom had also imprinted his own brain-pattern into the Quaza in Makuro's possession as part of an elaborate plan to get revenge on the sole survivor of the heroes that defeated him.
Hero Factory is soon formed, but Makuro's young daughter died from illness. In his grief, she ends up imprinted into the Quaza, and is later reborn as Natalie Breez. Makuro as a partial result of his despair would fully abandon flesh and blood and become a brain preserved in a cybernetic body. Meanwhile, Black Phantom's consciousness is born as Von Ness, who would later betray Hero Factory to become Von Nebula, an unwitting pawn to Black Phantom's ultimate revenge.
From here on, a lot of the same events as the original series happens, but with a bunch of other weird shit and different contexts because I felt like it:
William Furno is actually a duplicate of XPlode, the original William Furno who went rogue. Furno would eventually find the truth and abandon Hero Factory to become a vigilante.
A lot of the villains in general are secretly former Heroes who were effectively abandoned by the Factory and labelled as the bad guys. Von Nebula's gang is mainly comprised of victims of this and he's ultimately trying to avenge their mistreatment.
Recon Team is secretly trying to take over Hero Factory by exposing much of Makuro's past crimes, including the villains being former heroes and the origins of Quaza. They realize Daniel Rocka would be against the coup and tried to kill two birds with one stone by causing him to crash on Quatros and having his remains expose Quaza's origins. They don't know that they're pawns to Black Phantom.
Witch Doctor isn't Aldous Witch, he's a native inhabitant of Quatros trying to defend his home from those wanting to drain it of Quaza.
The Breakout has catastrophic ramifications as a lot of secrets coming out causes Hero Factory's standing to completely collapse; the villains effectively take over Makuhero City as its protectors while the Heroes either go on the run or join the villains.
And as mentioned before all of this is basically Black Phantom's elaborate plot to take down Makuro for defeating him decades ago. In fact, Black Phantom's been long dead. He's now basically an AI copy of himself piloting his armor, but since only his biometrics can make the suit function his skeletal remains are in there. My take on him is that much of a hater.
So basically, my idea for a Hero Factory fanon is that all that shit happened and now the Heroes (and villains) need to find a way to settle their differences and all their hangups about their origins to fight an evil French skeleton in a suit of armor before he can fully wreak havoc on a defenseless galaxy.
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Cross-posting an ACX comment I wrote, since it may be of more general interest. About ChatGPT, RLHF, and Redwood Research's violence classifier.
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[OpenAI's] main strategy was the same one Redwood used for their AI - RLHF, Reinforcement Learning by Human Feedback.
Redwood's project wasn't using RLHF. They were using rejection sampling. The "HF" part is there, but not the "RL" part.
In Redwood's approach,
You train a classifier using human feedback, as you described in your earlier post
Then, every time the model generates text, you ask the classifier "is this OK?"
If it says no, you ask the model to generate another text from the same prompt, and give it to the classifier
You repeat this over and over, potentially many times (Redwood allowed 100 iterations before giving up), until the classifier says one of them is OK. This is the "output" that the user sees.
In RLHF,
You train a classifier using human feedback, as you described in your earlier post. (In RLHF you call this "the reward model")
You do a second phase of training with your language model. In this phase, the language model is incentivized both to write plausible text, and to write text that the classifier will think is OK, usually heavily slanted toward the latter.
The classifier only judges entire texts at once, retrospectively. But language models write one token at a time. This is why it's "reinforcement learning": the model has to learn to write token-by-token a way that will ultimately add up to an acceptable text, while only getting feedback at the end.
(That is, the classifier doesn't make judgments like "you probably shouldn't have selected that word" while the LM is still writing. It just sits silently as the LM writes, and then renders a judgment on the finished product. RL is what converts this signal into token-by-token feedback for the LM, ultimately instilling hunches of the form "hmm, I probably shouldn't select this token at this point, that feels like it's going down a bad road.")
Every time the model generates text, you just … generate text like usual with an LM. But now, the "probabilities" coming out of the LM aren't just expressing how likely things are in natural text -- they're a mixture of that and the cover-your-ass "hunches" instilled by the RL training.
This distinction matters. Rejection sampling is more powerful than RLHF at suppressing bad behavior, because it can look back and notice bad stuff after the fact.
RLHF stumbles along trying not to "go down a bad road," but once it's made a mistake, it has a hard time correcting itself. From the examples I've seen from RLHF models, it feels like they try really hard to avoid making their first mistake, but then once they do make a mistake, the RL hunches give up and the pure language modeling side entirely takes over. (And then writes something which rejection sampling would know was bad, and would reject.)
(I don't think the claim that "rejection sampling is more powerful than RLHF at suppressing bad behavior" is controversial? See Anthropic's Red Teaming paper, for example. I use rejection sampling in nostalgebraist-autoresponder and it works well for me.)
Is rejection sampling still not powerful enough to let "the world's leading AI companies control their AIs"? Well, I don't know, and I wouldn't bet on its success. But the experiment has never really been tried.
The reason OpenAI and co. aren't using rejection sampling isn't that it's not powerful, it's that it is too costly. The hope with RLHF is that you do a single training run that bakes in the safety, and then sampling is no slower than it was before. With rejection sampling, every single sample may need to be "re-rolled" -- once or many times -- which can easily double or triple or (etc.) your operating costs.
Also, I think some of the "alien" failure modes we see in ChatGPT are specific to RLHF, and wouldn't emerge with rejection sampling.
I can't imagine it's that hard for a modern ML classifier to recognize that the bad ChatGPT examples are in fact bad. Redwood's classifier failed sometimes, but it's failures were much weirder than "the same thing but as a poem," and OpenAI could no doubt make a more powerful classifier than Redwood's was.
But steering so as to avoid an accident is much harder than looking at the wreck after the fact, and saying "hmm, looks like an accident happened." In rejection sampling, you only need to know what a car crash looks like; RLHF models have to actually drive the car.
(Sidenote: I think there might be some sort of rejection sampling layer used in ChatGPT, on top of the RLHF. But if so it's being used with a much more lenient threshold than you would use if you were trying to replace RLHF with rejection sampling entirely.)
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Masterpost 17
General asks
S/O pretends they're in love with skeleton just to kill him and his brother (UT, US, UF, HT, SF, FSG Sans & Papyrus)
Skeleton's teenager tries to prank his dad with a bucket above the door (UT, US, UF, HT, SF, FSG Sans & Papyrus)
Oak forgot his dead S/O when they came back as a skeleton (HT Sans)
S/O's parents are anti-monster and threats to hurt skeleton's brother (UT, US, UF, HT, SF, FSG Sans & Papyrus)
S/O and skeleton fell ill at the same time (UT, US, UF, HT, SF, FSG Sans & Papyrus)
Skeleton put salt into S/O's coffee as a prank but S/O drinks it anyway (UT Sans, US Papyrus, UF Sans, HT Sans, SF Papyrus, FSG Papyrus)
Character's child had a bad dream (UT characters)
Skeleton tries to win a plush for S/O in a festival but never succeed, S/O does on their first attempt (UT, US, UF, HT, SF, FSG Sans & Papyrus)
S/O accidentally send a love declaration by message to the wrong skeleton (UT, US, UF, HT, SF, FSG Sans & Papyrus)
Skeleton kisses goodbye S/O but they just wanted him to not forget his lunch (UT, US, UF, HT, SF, FSG Sans & Papyrus)
Skeleton and S/O are burning the kitchen down just when skeleton's brother is coming home (UT, US, UF, HT, SF, FSG Sans & Papyrus)
It's an Halloween party except there's a real zombie (UT characters)
S/O and skeleton are eating spaghettis like in the lady and the tramp (UT, US, UF, HT, SF, FSG Sans & Papyrus)
Skeleton's child had a bad dream (US, UF, HT, SF, FSG Sans & Papyrus)
S/O breaks in skeleton's room in the middle of the night (UT, US, UF, HT, SF, FSG Sans & Papyrus)
S/O pretends to love skeleton to scam and ruin him (UT, US, UF, HT, SF, FSG Sans & Papyrus)
S/O invites skeleton for Christmas to meet their family (UT, US, UF, HT, SF, FSG Sans & Papyrus)
Skeleton is sneaking their werewolf S/O out of a dog shelter (UT, US, UF, HT, SF, FSG Sans & Papyrus)
There's a random child in skeleton's house calling him dad and eating breakfast (UT, US, UF, HT, SF, FSG Sans & Papyrus)
Injury prompts event
Staying the night in case you need help (HT Toriel)
Using your hand to lift up their face to check for any injury, when you notice how pretty their eyes are, causing you to blush (UF Papyrus)
Dragging them to the nearest hospital because they're too stubborn to go themselves (HT Sans & Papyrus)
Trying to hide an injury (SF Sans)
Who did this to you? (UT Sans & Papyrus)
Carrying your wounded ennemy on your back (UF Papyrus & Burgerpants)
Noticing some scars on their back (UT Papyrus)
Dragging them to the nearest hospital because they're too stubborn to go themselves (SF Sans)
Go to sleep, you need rest (US Sans)
I thought I lost you (HT Sans & Papyrus)
How long have you been hiding this? (UT Sans & Papyrus)
Hugging them tightly, telling them how worried you were (SF Sans)
I hate to be a burden (SF Sans)
How long have you been hiding this? (UF Sans & Papyrus)
I don't know it was just there when I woke up (UF Papyrus)
Scolding them for their reckless actions, while they look at you, smiling softly (UF Sans)
Emoji event
Do they cry easily? (UT, US, HT, SF Papyrus)
What's a side of your oc that they don't want to show other people? (UF, HT, SF Sans & Papyrus)
What is something your oc will refuse to stay quiet about? (UT Sans)
How good are they at swimming? (UT, UF Undyne & Alphys)
Do they enjoy having their picture taken? (SF, FSG Sans)
How were they at school? (UT Sans & Papyrus)
When scared do they go flight or fight? (HT, HS, HF Sans & Papyrus)
Do they still have any object from their childhood? (UT Papyrus, D!Papyrus, DuT Sans, Killer Sans)
Are they a morning person? (MT, MF Sans & Papyrus)
Do they miss their S/O easily? (HT, HS, HF Sans & Papyrus)
See-Speak-Hear no evil (FSG Sans & Papyrus)
Other things
AI Papyrus wants you to cry
My Bitty Fell Sans AI
Myfanwi talks
Writing romance when you're aroace
A little glimpse of my next Underfell fanfiction
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AMD EPYC Processors Widely Supported By Red Hat OpenShift
EPYC processors
AMD fundamentally altered the rules when it returned to the server market in 2017 with the EPYC chip. Record-breaking performance, robust ecosystem support, and platforms tailored for contemporary workflows allowed EPYC to seize market share fast. AMD EPYC began the year with a meagre 2% of the market, but according to estimates, it now commands more than 30% of the market. All of the main OEMs, including Dell, HPE, Cisco, Lenovo, and Supermicro, offer EPYC CPUs on a variety of platforms.
Best EPYC Processor
Given AMD EPYC’s extensive presence in the public cloud and enterprise server markets, along with its numerous performance and efficiency world records, it is evident that EPYC processors is more than capable of supporting Red Hat OpenShift, the container orchestration platform. EPYC is the finest option for enabling application modernization since it forms the basis of contemporary enterprise architecture and state-of-the-art cloud functionalities. Making EPYC processors argument and demonstrating why AMD EPYC should be taken into consideration for an OpenShift implementation at Red Hat Summit was a compelling opportunity.
Gaining market share while delivering top-notch results
Over the course of four generations, EPYC’s performance has raised the standard. The fastest data centre CPU in the world is the AMD EPYC 4th Generation. For general purpose applications (SP5-175A), the 128-core EPYC provides 73% better performance at 1.53 times the performance per projected system watt than the 64-core Intel Xeon Platinum 8592+.
In addition, EPYC provides the leadership inference performance needed to manage the increasing ubiquity of AI. For example, utilising the industry standard end-to-end AI benchmark TPCx-AI SF30, an Intel Xeon Platinum 8592+ (SP5-051A) server has almost 1.5 times the aggregate throughput compared to an AMD EPYC 9654 powered server.
A comprehensive array of data centres and cloud presence
You may be certain that the infrastructure you’re now employing is either AMD-ready or currently operates on AMD while you work to maximise the performance of your applications.
Red Hat OpenShift-certified servers are the best-selling and most suitable for the OpenShift market among all the main providers. Take a time to look through the Red Hat partner catalogue, if you’re intrigued, to see just how many AMD-powered choices are compatible with OpenShift.
On the cloud front, OpenShift certified AMD-powered instances are available on AWS and Microsoft Azure. For instance, the EPYC-powered EC2 instances on AWS are T3a, C5a, C5ad, C6a, M5a, M5ad, M6a, M7a, R5a, and R6a.
Supplying the energy for future tasks
The benefit AMD’s rising prominence in the server market offers enterprises is the assurance that their EPYC infrastructure will perform optimally whether workloads are executed on-site or in the cloud. This is made even more clear by the fact that an increasing number of businesses are looking to jump to the cloud when performance counts, such during Black Friday sales in the retail industry.
Modern applications increasingly incorporate or produce AI elements for rich user benefits in addition to native scalability flexibility. Another benefit of using AMD EPYC CPUs is their shown ability to provide quick large language model inference responsiveness. A crucial factor in any AI implementation is the latency of LLM inference. At Red Hat Summit, AMD seized the chance to demonstrate exactly that.
AMD performed Llama 2-7B-Chat-HF at bf16 precisionover Red Hat OpenShift on Red Hat Enterprise Linux CoreOS in order to showcase the performance of the 4th Gen AMD EPYC. AMD showcased the potential of EPYC on several distinct use cases, one of which was a chatbot for customer service. The Time to First Token in this instance was 219 milliseconds, easily satisfying the patience of a human user who probably anticipates a response in under a second.
The maximum performance needed by the majority of English readers is approximately 6.5 tokens per second, or 5 English words per second, but the throughput of tokens was 8 tokens per second. The model’s performance can readily produce words quicker than a fast reader can usually keep up, as evidenced by the 127 millisecond latency per token.
Meeting developers, partners, and customers at conferences like Red Hat Summit is always a pleasure, as is getting to hear directly from customers. AMD has worked hard to demonstrate that it provides infrastructure that is more than competitive for the development and deployment of contemporary applications. EPYC processors, EPYC-based commercial servers, and the Red Hat Enterprise Linux and OpenShift ecosystem surrounding them are reliable resources for OpenShift developers.
It was wonderful to interact with the community at the Summit, and it’s always positive to highlight AMD’s partnerships with industry titans like Red Hat. EPYC processors will return this autumn with an update, coinciding with Kubecon.
Red Hat OpenShift’s extensive use of AMD EPYC-based servers is evidence of their potent blend of affordability, effectiveness, and performance. As technology advances, they might expect a number of fascinating breakthroughs in this field:
Improved Efficiency and Performance
EPYC processors of the upcoming generation
AMD is renowned for its quick innovation cycle. It’s expected that upcoming EPYC processors would offer even more cores, faster clock rates, and cutting-edge capabilities like AI acceleration. Better performance will result from these developments for demanding OpenShift workloads.
Better hardware-software integration
AMD, Red Hat, and hardware partners working together more closely will produce more refined optimizations that will maximize the potential of EPYC-based systems for OpenShift. This entails optimizing virtualization capabilities, I/O performance, and memory subsystems.
Increased Support for Workloads
Acceleration of AI and machine learning
EPYC-based servers equipped with dedicated AI accelerators will proliferate as AI and ML become more widespread. As a result, OpenShift environments will be better equipped to manage challenging AI workloads.
Data analytics and high-performance computing (HPC)
EPYC’s robust performance profile makes it appropriate for these types of applications. Platforms that are tailored for these workloads should be available soon, allowing for OpenShift simulations and sophisticated analytics.
Integration of Edge Computing and IoT
Reduced power consumption
EPYC processors of the future might concentrate on power efficiency, which would make them perfect for edge computing situations where power limitations are an issue. By doing this, OpenShift deployments can be made closer to data sources, which will lower latency and boost responsiveness.
IoT device management
EPYC-based servers have the potential to function as central hubs for the management and processing of data from Internet of Things devices. On these servers, OpenShift can offer a stable foundation for creating and implementing IoT applications.
Environments with Hybrid and Multiple Clouds
Uniform performance across clouds
major cloud providers will probably offer EPYC-based servers, which will guarantee uniform performance for hybrid and multi-cloud OpenShift setups.
Cloud-native apps that are optimised
EPYC-based platforms are designed to run cloud-native applications effectively by utilising microservices and containerisation.
Read more on govindhtech.com
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Europe Aircraft Communication System Market Value Research to Develop Rapidly by Forecast (2024-2032)
Europe's aircraft communication system market is poised for rapid development and expansion from 2024 to 2032, driven by technological innovation, regulatory initiatives, and the region's strategic focus on enhancing aviation safety and efficiency.
Technological Advancements Driving Growth
The European aircraft communication system market is benefiting from continuous advancements in communication technologies tailored for aviation. From VHF (Very High Frequency) and HF (High Frequency) radios to satellite-based communication systems and digital datalinks, these technologies play a crucial role in facilitating seamless communication between aircraft, air traffic controllers, and ground operations.
New developments in software-defined radios (SDR) and voice-over-IP (VoIP) technologies are enhancing the flexibility and scalability of communication systems, enabling interoperability and integration with emerging air traffic management platforms. These advancements not only improve communication reliability but also support the implementation of advanced navigation and surveillance systems across European airspace.
Market Expansion Across Regions
Across Europe, major aviation hubs such as London, Paris, Frankfurt, and Amsterdam are pivotal in driving market demand for aircraft communication systems. These cities host extensive air traffic operations, bustling airports, and critical aviation infrastructure, necessitating robust communication solutions to ensure safe and efficient flight operations.
Furthermore, regulatory initiatives by the European Union Aviation Safety Agency (EASA) and national aviation authorities are mandating the adoption of modern communication standards and cybersecurity protocols. Compliance with these regulations is spurring investment in next-generation communication technologies and fostering partnerships between airlines, technology providers, and government agencies.
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Forecasting Market Growth
Looking ahead to 2032, the European aircraft communication system market is projected to witness substantial growth. Factors such as increasing air travel demand, the expansion of low-cost carriers, and investments in airport infrastructure will drive market expansion across the region. The integration of advanced communication systems with emerging technologies, including AI-driven analytics and cloud-based solutions, will further enhance operational efficiency and passenger connectivity.
Moreover, initiatives focusing on sustainable aviation and carbon-neutral operations will influence market dynamics, prompting airlines to invest in fuel-efficient aircraft equipped with advanced communication capabilities. These initiatives align with Europe's broader strategy to achieve environmental sustainability and enhance aviation safety through innovative technology solutions.
In conclusion, the European aircraft communication system market presents lucrative opportunities for stakeholders from 2024 to 2032. By leveraging technological advancements, navigating regulatory landscapes, and fostering strategic collaborations, stakeholders can capitalize on the region's growing demand for advanced communication solutions and drive sustainable growth in the aviation industry.
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Optimizing LLM Deployment: vLLM PagedAttention and the Future of Efficient AI Serving
New Post has been published on https://thedigitalinsider.com/optimizing-llm-deployment-vllm-pagedattention-and-the-future-of-efficient-ai-serving/
Optimizing LLM Deployment: vLLM PagedAttention and the Future of Efficient AI Serving
Large Language Models (LLMs) deploying on real-world applications presents unique challenges, particularly in terms of computational resources, latency, and cost-effectiveness. In this comprehensive guide, we’ll explore the landscape of LLM serving, with a particular focus on vLLM (vector Language Model), a solution that’s reshaping the way we deploy and interact with these powerful models.
The Challenges of Serving Large Language Models
Before diving into specific solutions, let’s examine the key challenges that make LLM serving a complex task:
Computational Resources
LLMs are notorious for their enormous parameter counts, ranging from billions to hundreds of billions. For instance, GPT-3 boasts 175 billion parameters, while more recent models like GPT-4 are estimated to have even more. This sheer size translates to significant computational requirements for inference.
Example:
Consider a relatively modest LLM with 13 billion parameters, such as LLaMA-13B. Even this model requires:
– Approximately 26 GB of memory just to store the model parameters (assuming 16-bit precision)
– Additional memory for activations, attention mechanisms, and intermediate computations
– Substantial GPU compute power for real-time inference
Latency
In many applications, such as chatbots or real-time content generation, low latency is crucial for a good user experience. However, the complexity of LLMs can lead to significant processing times, especially for longer sequences.
Example:
Imagine a customer service chatbot powered by an LLM. If each response takes several seconds to generate, the conversation will feel unnatural and frustrating for users.
Cost
The hardware required to run LLMs at scale can be extremely expensive. High-end GPUs or TPUs are often necessary, and the energy consumption of these systems is substantial.
Example:
Running a cluster of NVIDIA A100 GPUs (often used for LLM inference) can cost thousands of dollars per day in cloud computing fees.
Traditional Approaches to LLM Serving
Before exploring more advanced solutions, let’s briefly review some traditional approaches to serving LLMs:
Simple Deployment with Hugging Face Transformers
The Hugging Face Transformers library provides a straightforward way to deploy LLMs, but it’s not optimized for high-throughput serving.
Example code:
from transformers import AutoModelForCausalLM, AutoTokenizer import torch model_name = "meta-llama/Llama-2-13b-hf" model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto") tokenizer = AutoTokenizer.from_pretrained(model_name) def generate_text(prompt, max_length=100): inputs = tokenizer(prompt, return_tensors="pt").to(model.device) outputs = model.generate(**inputs, max_length=max_length) return tokenizer.decode(outputs[0], skip_special_tokens=True) print(generate_text("The future of AI is"))
While this approach works, it’s not suitable for high-traffic applications due to its inefficient use of resources and lack of optimizations for serving.
Using TorchServe or Similar Frameworks
Frameworks like TorchServe provide more robust serving capabilities, including load balancing and model versioning. However, they still don’t address the specific challenges of LLM serving, such as efficient memory management for large models.
Understanding Memory Management in LLM Serving
Efficient memory management is critical for serving large language models (LLMs) due to the extensive computational resources required. The following images illustrate various aspects of memory management, which are integral to optimizing LLM performance.
Segmented vs. Paged Memory
These two diagrams compare segmented memory and paged memory management techniques, commonly used in operating systems (OS).
Segmented Memory: This technique divides memory into different segments, each corresponding to a different program or process. For instance, in an LLM serving context, different segments might be allocated to various components of the model, such as tokenization, embedding, and attention mechanisms. Each segment can grow or shrink independently, providing flexibility but potentially leading to fragmentation if segments are not managed properly.
Paged Memory: Here, memory is divided into fixed-size pages, which are mapped onto physical memory. Pages can be swapped in and out as needed, allowing for efficient use of memory resources. In LLM serving, this can be crucial for managing the large amounts of memory required for storing model weights and intermediate computations.
Memory Management in OS vs. vLLM
This image contrasts traditional OS memory management with the memory management approach used in vLLM.
OS Memory Management: In traditional operating systems, processes (e.g., Process A and Process B) are allocated pages of memory (Page 0, Page 1, etc.) in physical memory. This allocation can lead to fragmentation over time as processes request and release memory.
vLLM Memory Management: The vLLM framework uses a Key-Value (KV) cache to manage memory more efficiently. Requests (e.g., Request A and Request B) are allocated blocks of the KV cache (KV Block 0, KV Block 1, etc.). This approach helps minimize fragmentation and optimizes memory usage, allowing for faster and more efficient model serving.
Attention Mechanism in LLMs
Attention Mechanism in LLMs
The attention mechanism is a fundamental component of transformer models, which are commonly used for LLMs. This diagram illustrates the attention formula and its components:
Query (Q): A new token in the decoder step or the last token that the model has seen.
Key (K): Previous context that the model should attend to.
Value (V): Weighted sum over the previous context.
The formula calculates the attention scores by taking the dot product of the query with the keys, scaling by the square root of the key dimension, applying a softmax function, and finally taking the dot product with the values. This process allows the model to focus on relevant parts of the input sequence when generating each token.
Serving Throughput Comparison
vLLM: Easy, Fast, and Cheap LLM Serving with PagedAttention
This image presents a comparison of serving throughput between different frameworks (HF, TGI, and vLLM) using LLaMA models on different hardware setups.
LLaMA-13B, A100-40GB: vLLM achieves 14x – 24x higher throughput than HuggingFace Transformers (HF) and 2.2x – 2.5x higher throughput than HuggingFace Text Generation Inference (TGI).
LLaMA-7B, A10G: Similar trends are observed, with vLLM significantly outperforming both HF and TGI.
vLLM: A New LLM Serving Architecture
vLLM, developed by researchers at UC Berkeley, represents a significant leap forward in LLM serving technology. Let’s explore its key features and innovations:
PagedAttention
At the heart of vLLM lies PagedAttention, a novel attention algorithm inspired by virtual memory management in operating systems. Here’s how it works:
– Key-Value (KV) Cache Partitioning: Instead of storing the entire KV cache contiguously in memory, PagedAttention divides it into fixed-size blocks.
– Non-Contiguous Storage: These blocks can be stored non-contiguously in memory, allowing for more flexible memory management.
– On-Demand Allocation: Blocks are allocated only when needed, reducing memory waste.
– Efficient Sharing: Multiple sequences can share blocks, enabling optimizations for techniques like parallel sampling and beam search.
Illustration:
“`
Traditional KV Cache:
[Token 1 KV][Token 2 KV][Token 3 KV]…[Token N KV]
(Contiguous memory allocation)
PagedAttention KV Cache:
[Block 1] -> Physical Address A
[Block 2] -> Physical Address C
[Block 3] -> Physical Address B
…
(Non-contiguous memory allocation)
“`
This approach significantly reduces memory fragmentation and allows for much more efficient use of GPU memory.
Continuous Batching
vLLM implements continuous batching, which dynamically processes requests as they arrive, rather than waiting to form fixed-size batches. This leads to lower latency and higher throughput.
Example:
Imagine a stream of incoming requests:
“`
Time 0ms: Request A arrives
Time 10ms: Start processing Request A
Time 15ms: Request B arrives
Time 20ms: Start processing Request B (in parallel with A)
Time 25ms: Request C arrives
…
“`
With continuous batching, vLLM can start processing each request immediately, rather than waiting to group them into predefined batches.
Efficient Parallel Sampling
For applications that require multiple output samples per prompt (e.g., creative writing assistants), vLLM’s memory sharing capabilities shine. It can generate multiple outputs while reusing the KV cache for shared prefixes.
Example code using vLLM:
from vllm import LLM, SamplingParams llm = LLM(model="meta-llama/Llama-2-13b-hf") prompts = ["The future of AI is"] # Generate 3 samples per prompt sampling_params = SamplingParams(n=3, temperature=0.8, max_tokens=100) outputs = llm.generate(prompts, sampling_params) for output in outputs: print(f"Prompt: output.prompt") for i, out in enumerate(output.outputs): print(f"Sample i + 1: out.text")
This code efficiently generates multiple samples for the given prompt, leveraging vLLM’s optimizations.
Benchmarking vLLM Performance
To truly appreciate the impact of vLLM, let’s look at some performance comparisons:
Throughput Comparison
Based on the information provided, vLLM significantly outperforms other serving solutions:
– Up to 24x higher throughput compared to Hugging Face Transformers
– 2.2x to 3.5x higher throughput than Hugging Face Text Generation Inference (TGI)
Illustration:
“`
Throughput (Tokens/second)
|
| ****
| ****
| ****
| **** ****
| **** **** ****
| **** **** ****
|————————
HF TGI vLLM
“`
Memory Efficiency
vLLM’s PagedAttention results in near-optimal memory usage:
– Only about 4% memory waste, compared to 60-80% in traditional systems
– This efficiency allows for serving larger models or handling more concurrent requests with the same hardware
Getting Started with vLLM
Now that we’ve explored the benefits of vLLM, let’s walk through the process of setting it up and using it in your projects.
6.1 Installation
Installing vLLM is straightforward using pip:
!pip install vllm
6.2 Basic Usage for Offline Inference
Here’s a simple example of using vLLM for offline text generation:
from vllm import LLM, SamplingParams # Initialize the model llm = LLM(model="meta-llama/Llama-2-13b-hf") # Prepare prompts prompts = [ "Write a short poem about artificial intelligence:", "Explain quantum computing in simple terms:" ] # Set sampling parameters sampling_params = SamplingParams(temperature=0.8, max_tokens=100) # Generate responses outputs = llm.generate(prompts, sampling_params) # Print the results for output in outputs: print(f"Prompt: output.prompt") print(f"Generated text: output.outputs[0].textn")
This script demonstrates how to load a model, set sampling parameters, and generate text for multiple prompts.
6.3 Setting Up a vLLM Server
For online serving, vLLM provides an OpenAI-compatible API server. Here’s how to set it up:
1. Start the server:
python -m vllm.entrypoints.openai.api_server --model meta-llama/Llama-2-13b-hf
2. Query the server using curl:
curl http://localhost:8000/v1/completions -H "Content-Type: application/json" -d ' "model": "meta-llama/Llama-2-13b-hf", "prompt": "The benefits of artificial intelligence include:", "max_tokens": 100, "temperature": 0.7 '
This setup allows you to serve your LLM with an interface compatible with OpenAI’s API, making it easy to integrate into existing applications.
Advanced Topics on vLLM
While vLLM offers significant improvements in LLM serving, there are additional considerations and advanced topics to explore:
7.1 Model Quantization
For even more efficient serving, especially on hardware with limited memory, quantization techniques can be employed. While vLLM itself doesn’t currently support quantization, it can be used in conjunction with quantized models:
from transformers import AutoModelForCausalLM, AutoTokenizer import torch # Load a quantized model model_name = "meta-llama/Llama-2-13b-hf" model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", load_in_8bit=True) tokenizer = AutoTokenizer.from_pretrained(model_name) # Use the quantized model with vLLM from vllm import LLM llm = LLM(model=model, tokenizer=tokenizer)
7.2 Distributed Inference
For extremely large models or high-traffic applications, distributed inference across multiple GPUs or machines may be necessary. While vLLM doesn’t natively support this, it can be integrated into distributed systems using frameworks like Ray:
import ray from vllm import LLM @ray.remote(num_gpus=1) class DistributedLLM: def __init__(self, model_name): self.llm = LLM(model=model_name) def generate(self, prompt, params): return self.llm.generate(prompt, params) # Initialize distributed LLMs llm1 = DistributedLLM.remote("meta-llama/Llama-2-13b-hf") llm2 = DistributedLLM.remote("meta-llama/Llama-2-13b-hf") # Use them in parallel result1 = llm1.generate.remote("Prompt 1", sampling_params) result2 = llm2.generate.remote("Prompt 2", sampling_params) # Retrieve results print(ray.get([result1, result2]))
7.3 Monitoring and Observability
When serving LLMs in production, monitoring is crucial. While vLLM doesn’t provide built-in monitoring, you can integrate it with tools like Prometheus and Grafana:
from prometheus_client import start_http_server, Summary from vllm import LLM # Define metrics REQUEST_TIME = Summary('request_processing_seconds', 'Time spent processing request') # Initialize vLLM llm = LLM(model="meta-llama/Llama-2-13b-hf") # Expose metrics start_http_server(8000) # Use the model with monitoring @REQUEST_TIME.time() def process_request(prompt): return llm.generate(prompt) # Your serving loop here
This setup allows you to track metrics like request processing time, which can be visualized in Grafana dashboards.
Conclusion
Serving Large Language Models efficiently is a complex but crucial task in the age of AI. vLLM, with its innovative PagedAttention algorithm and optimized implementation, represents a significant step forward in making LLM deployment more accessible and cost-effective.
By dramatically improving throughput, reducing memory waste, and enabling more flexible serving options, vLLM opens up new possibilities for integrating powerful language models into a wide range of applications. Whether you’re building a chatbot, a content generation system, or any other NLP-powered application, understanding and leveraging tools like vLLM will be key to success.
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Top Trends in the Heart Failure Major Market for 2024
Heart failure (HF) remains a significant global health concern, affecting millions and imposing a heavy burden on healthcare systems. However, the landscape of the heart failure market is undergoing a dynamic transformation, driven by innovation and a growing focus on improved patient outcomes.
Buy Full Report to Know More About the Heart Failure Market Forecast
Download a Free Report Sample
Here's a glimpse into the top trends shaping this market in 2024:
1. The Rise of Minimally Invasive Interventions:
Minimally Invasive Valve Replacement (MIVR): Traditional open-heart surgery for valve replacement is being challenged by MIVR procedures. These minimally invasive techniques offer faster recovery times, reduced patient discomfort, and potentially improved long-term outcomes.
Transcatheter Aortic Valve Replacement (TAVR): TAVR is a well-established MIVR option for aortic valve stenosis, particularly for high-risk patients who may not be suitable for open-heart surgery. Advancements in technology are enabling broader patient application of TAVR procedures.
Percutaneous Mitral Valve Repair (PMVR): PMVR is a newer technique gaining traction for mitral valve regurgitation. This minimally invasive approach offers a less invasive alternative to traditional mitral valve surgery.
2. Precision Medicine and Personalized Care:
Genetic Testing and Tailored Therapies: Identifying the underlying genetic causes of heart failure allows for more targeted treatment approaches. This could involve personalized medication regimens or therapies aimed at addressing specific genetic risk factors.
Remote Monitoring and Telehealth Solutions: Wearable devices and remote monitoring technologies allow for continuous patient monitoring, enabling early detection of potential complications and facilitating timely interventions. Telehealth consultations offer improved access to specialist care, particularly in remote areas.
3. The Growing Focus on Heart Failure Prevention:
Early Detection and Risk Management: Emphasis is shifting towards early detection of heart failure risk factors like hypertension, diabetes, and obesity. This allows for lifestyle modifications, medication management, and preventative measures to potentially delay or even prevent the onset of heart failure.
4. Innovation in Cardiac Devices and Technologies:
Next-Generation Ventricular Assist Devices (VADs): VADs are implanted pumps that assist the heart in pumping blood. Advancements in VAD technology are leading to smaller, more efficient, and quieter devices with improved long-term outcomes for patients.
Artificial Intelligence (AI) in Diagnostics and Treatment: AI algorithms are being used to analyze patient data, predict potential complications, and personalize treatment plans. AI-powered tools can also assist with early detection of heart failure based on medical scans or patient monitoring data.
5. Evolving Healthcare Delivery Models:
Focus on Value-Based Care: There's a growing emphasis on healthcare models that focus on patient outcomes and value delivered, rather than simply volume of procedures. This incentivizes the development of more effective and cost-efficient treatment strategies for heart failure.
The Rise of Cardiac Rehabilitation Programs: Comprehensive cardiac rehabilitation programs play a crucial role in improving patient outcomes and quality of life after a heart failure event. These programs combine exercise therapy, education, and psychological support to help patients manage their condition and live longer, healthier lives.
Conclusion:
The heart failure market is brimming with promising advancements. The focus on minimally invasive procedures, personalized care, preventative measures, and innovative technologies offers hope for improved patient outcomes and a brighter future for those living with heart failure. As these trends continue to evolve, the heart failure market will play a vital role in alleviating the burden of this global health challenge.
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Abarth 600e Scorpionissima si mostra per l’anniversario dei 75 anni del Costruttore
Abarth ha celebrato l’anniversario della sua fondazione. E sono arrivate nuove immagini, di esterni e interni, per la compatta tutto pepe.
Un compleanno importante, Abarth rappresenta uno storico riferimento per elaborazioni, kit estetici e modelli personalizzati con uno stile sportivo e riconoscibile. Il primo passo verso la nuova epoca solo elettrica, con la Abarth 500e, al momento non è stato molto felice, la nuova 600e Scorpionissima, che arriverà sul mercato a giugno, punta a mietere più consensi, forte anche di oltre il 50% di potenza in più.
Abarth e non solo: una piattaforma per tre sportive italiane
Un primato lo detiene ancora prima di arrivare: è l’Abarth più potente della storia con i suoi 240 cavalli, nascendo sulla piattaforma Perfo-eCmp, evoluzione della eCmp. Su questa architettura, a trazione anteriore, ma con differenziale a slittamento limitato appositamente dedicato, nasceranno anche altre due piccole sportive italiane quali la Alfa Romeo Milano Quadrifoglio e la Lancia Ypsilon HF.
Abarth 600e Scorpionissima avrà una accelerazione da 0 a 100 km/h inferiore ai 6 secondi, con sterzo, assetto e freni dedicati: più ancorata a terra e con carreggiate probabilmente più larghe.
Abarth 600e Scorpionissima sarà mezzo metro più lunga rispetto a 500e che è lunga 3,67 metri: Fiat 600e è 4,17 metri. In abitacolo risaltano i sedili sportivi, in pelle e Alcantaracon fianchetti contenitivi, mentre il volante riprende quello della 500e, con una plancia più aggressiva grazie all’inserto nero opaco.
Presenti iltunnel centrale provvisto con una copertura per stivare oggetti, una luce ambiente dedicata e la radio NAV da 10 pollici, con grafiche dedicate e pagine di misurazione delle performance. Non mancherà il discusso Sound Generator che riprodurrà il suono dei motori termici Abarth: attivabile e disattivabile.
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Jimi in Space
Generated by AI Comic Factory - a Hugging Face Space by jbilcke-hf
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The MAL x HF 2023 contest ends in 7 days! [Checklist]
This year's MyAnimeList x Honeyfeed Writing Contest novel submission period closes this next Thursday, August 31st. If you are participating in this contest, here's a checklist of important things to remind yourself of what your novel needs to be eligible for the judging process.
Your novel's protagonist is a male character and the story is told from the male POV.
Your novel revolves mostly around romance, where the MC's main focus is to have a wholesome romantic relationship. Love is in the air most of the time, and it's the main drive of your story.
On your Author's Note, it should clearly say what subplot and theme you are entering. If your novel does not display the subplot "Isekai" or "Present-Day" accompanied by the appropriate themes it will get automatically disqualified. For Isekai, the themes are RPG or High Fantasy. For Present-Day, the themes are Chance Encounter or Teenage Love.
Example of how a subplot and theme should look like on your contest entry Author's Note:
Note about Author's Note:
If you deleted the auto-text input from your author's note from your novel when entering the contest, you can manually input it again by following the exact format shown in the example above. Please keep in mind that if your novel does not have this information in the author's note by August 31, 2023, your entry is automatically disqualified.
Note about the Isekai subplot:
All Isekai subplot entries must follow the Isekai trope of arriving into another world by reincarnation, summoning, ritual, portal, curse, etc., and the protagonist can not easily go back to the "real world" or "jump between worlds" willingly. The MC can not just be an original local from that fantasy land. The only exception to this is that your protagonist is locked inside a video game world while his body is inactive in the real world or controlled by another consciousness other than the MC's. The "being isekai'd" is a must for this type of contest entry.
Note about RPG theme:
All RPG entries must have LitRPG elements or a videogame characteristic clearly presented in the story. These RPG concepts are leveling systems, skill points, skill trees, scores, ranks, health bars, experience-gaining, video-game-like menus, etc.
Note about the Present-Day subplot:
All Present-Day subplot novels must be set in a contemporary real world, meaning that your character is living on planet Earth in the year 2023. Mentions of supernatural elements are okay when sparse and are not the main focus of the story. Things like ghosts, aliens, spirits, illusions, wishes, miracles, etc. are okay in moderation, but things like fantasy creatures and magic being real are less okay. The use of fantasy elements in Present-Day entries will be discussed case by case by the judges.
4. Your Novel is not published anywhere else other than Honeyfeed until October 30th, 2023 (for non-finalists).
Note about Finalists:
Those novels that make it to the finalist 10 can not be posted outside of Honeyfeed until the winners are revealed in December 2023. If your finalist novel is discovered to be posted on another website before the winners are announced, it will be automatically disqualified from the finalists vote.
5. Your novel has an appealing synopsis.
6. Your novel has a cover image with the appropriate artist credit.
Note about copyrighted images:
You can not just get an "image off the internet" and use it as your novel cover without the author's explicit consent. If you are found using a copyrighted image that does not belong to you, your novel will be automatically disqualified. In some cases, we may ask for proof of purchase of the art or the artist's direct contact information. Please use AI-generated art at your own risk.
Note about Canva:
Canva is free and it is available directly on the Honeyfeed site. Please use it if you don't want to pay for art.
7. Your chapters were not all posted on the same day.
8. Your novel's main plot point was resolved within 25,000 words minimum or 75,000 words maximum.
Note about min/max wording limits:
Honeyfeed is flexible if your novel is a few hundred words short or over. Your story doesn't have to make it exactly at 25k/75k words when its finished. A few words under or over is okay, just don't abuse the flexibility and be safe by complying with the limits as best as you can.
9. Your novel reaches a satisfactory ending or volume closure by August 31, 2023.
10. You do not update your novel after August 31, 2023.
Note about updating Author's Note or Cover Image:
When you update your novel's cover or author's note, Honeyfeed does not know where the update happened so it marks it as a new entire novel update. When updating either of those, the novel will appear as updated after August 31st. If you update your author's note, please do not delete the subplot or theme. If you update your novel cover, please do not leave your novel coverless. If you do end up updating any of those after Aug.31, please leave a small note on your Author's Note with what has been updated on what date, so that the judges know what got updated. Judges do not have backend access to Honeyfeed.
We invite you to re-read all of the MAL x Honeyfeed Writing Contest details and rules.
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Cairns Marine Electronics
Cairns Marine Electronics is a mobile electronics business, specialising in marine equipment.
Sales, Installations and repairs to the following equipement:
GPS
VHF and HF Radio
VMS
Chart plotters
Radar
Sonar
Sounders
Auto pilots
Multifunction Devices
AIS
Marine solar
Wind gererators
Satellite communications
NMEA
General DC wiring
We can repair to component level
Rates: $110 per hour (Inc GST) during business hours. After hour call out rates will apply
All call out inspections, repairs require an upfront minimum charge of $110.00 (Inc GST)
We charge a minimum $50.00 Inc GST for diagosing any equipement dropped of or delivered.
We guarantee our work
Mobile servicing in the Cairns region
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6G-Drahtlose Technologie der nächsten Generation kann den menschlichen Körper zur Energiegewinnung nützen
Forscher der Universität von Massachusetts Amherst (UMass Amherst) nutzen den Körper, um Restenergie zu gewinnen und tragbare Geräte mit Strom zu versorgen
Während Sie möglicherweise gerade erst damit beginnen, die Vorteile der 5G-Funk-Technologie zu nutzen, arbeiten Forscher weltweit bereits intensiv an der Technologie der Zukunft: 6G
Einer der vielversprechendsten Durchbrüche in der 6G-Telekommunikation ist die Möglichkeit der Visible Light Communication (VLC), was nahezu einer drahtlosen Version von Glasfaseroptik entspricht und Lichtblitze zur Übertragung von Informationen verwendet. Jetzt hat ein Forscherteam der genannten Universität bekannt gegeben, dass sie eine kostengünstige, innovative Methode erfunden haben, um die Restenergie von VLC zu nutzen, indem der menschliche Körper als Antenne verwendet wird. Diese Restenergie kann recycelt werden, um eine Reihe von tragbaren Geräten oder vielleicht sogar größerer Elektronik mit Strom zu versorgen.
https://rumble.com/v2mbgfy-6-g-die-zukunft-des-internets.html
„VLC ist ziemlich einfach und interessant“, berichtet Jie Xiong, Professor für Informations- und Computerwissenschaften an der UMass Amherst und leitender Autor der Publikation. Anstelle der Verwendung von Funksignalen, um Informationen drahtlos zu übermitteln, nutzt es das Licht von LEDs, die sich bis zu einer Million Mal pro Sekunde ein- und ausschalten können. Der Reiz von VLC besteht auch darin, dass die Infrastruktur bereits überall vorhanden ist - unsere Häuser, Fahrzeuge, Straßenbeleuchtung und Büros werden alle mittels LED Lampen beleuchtet, die auch Daten übertragen könnten. „Alles was eine integrierte Kamera hat, wie zum Beispiel unsere Smartphones, Tablets oder Laptops, könnten als Empfänger agieren“, sagt Xiong.
Zuvor zeigten Xiong und Erstautor Minhao Cui, ein Doktorand der Informations- und Informatikwissenschaften an der UMass Amherst, dass es in VLC-Systemen zu erheblichen Energieverlusten kommt, da die LEDs auch Seitenkanal-HF-Signale oder Funkwellen aussenden. Wenn diese ausgetretene HF-Energie abgesaugt werden könnte, stünde sie zur Nutzung bereit.
Nach unterschiedlichen Versuchen, eine Antenne zu entwerfen, um die ausgetretene HF zu sammeln und zu verstärken, die allesamt nicht den gewünschten Effekt erzielten, kam Cui schlussendlich auf die Idee zu experimentieren, was geschehen würde, wenn die Spule mit einem menschlichen Körper in Kontakt kommt. Dabei wurde augenblicklich klar, dass ein menschlicher Körper das beste Medium ist, um die Leistung der Spule zu verstärken, die ausgetretene HF-Energie zu sammeln, nämlich bis zum zehnfachen als die bloße Spule allein.
Nach vielen Experimenten entwickelte das Team Bracelet+, eine einfache Spule aus Kupferdraht, die als Armband am oberen Unterarm getragen wird. Während unterschiedliche Designs zum Tragen als Ring, Gürtel, Fußkettchen oder Halskette in Betracht kommen, scheint das Armband die richtige Balance zwischen Energiegewinnung und Tragbarkeit in sich zu vereinen.
Das Design ist billig, weniger als 50 Cent, stellen die Autoren fest, wobei ihr Artikel von der Association for Computing Machinery’s Conference on Embedded Networked Sensor Systems mit dem renommierten Best Paper Award ausgezeichnet wurde. Aber Bracelet+ kann bis zu Mikrowatt erreichen, genug, um viele Sensoren zu unterstützen, wie z.B. am Körper getragene Sensoren zur gesundheitlichen Überwachung, die aufgrund ihrer niedrigen Abtastrate und langen Dauer des Schlafmodus mit wenig Leistung auskommen.
„Letztendlich wollen wir in der Lage sein, Restenergie aus allen möglichen Quellen zu gewinnen, um zukünftige Technologien zu speisen“, sagt Xiong.
4. Januar 2023
Übersetzung von: @JM
https://der-schandstaat.info/geoffrey-hinton-der-godfather-of-ai-kuendigt-bei-google-und-bereut-sein-lebenswerk/
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Skyrim SSE mod list for new playthrough.
This is the modlist and loadorder for my new Skyrim SE playthrough. Some of the ESP are not active because they are included in a merged plugin to save space but left on this list to show they have been included. There are also a few mods showing up in the load order that aren’t in the plugin list because while I wanted to include them, the build wasn’t stable enough while including them. (That doesn’t mean these mods are bad or that you shouldn’t try them, just that my load order has far to much going on in it to support that many resource heavy mods.)
Plug in Load Order - # This file was automatically generated by Mod Organizer.
Skyrim.esm
Update.esm
Dawnguard.esm
HearthFires.esm
Dragonborn.esm
Unofficial Skyrim Special Edition Patch.esp
Skyrim Project Optimization - Full Version.esm
RSkyrimChildren.esm
UHDAP - en0.esp
UHDAP - en1.esp
UHDAP - en2.esp
UHDAP - en3.esp
UHDAP - en4.esp
UHDAP - MusicHQ.esp
Landscape and Water Fixes.esp
MajesticMountains_Landscape.esm
AHZmoreHUD.esl
LegacyoftheDragonborn.esm
Cathedral - 3D Mountain Flowers.esp
MajesticMountains_Moss.esp
RealisticWaterTwo - Resources.esm
DA_Skyship.esm
FarmhouseChimneys.esp
ImCh.esm
Campfire.esm
Falskaar.esm
Vigilant.esm
Apachii_DivineEleganceStore.esm
WheelsOfLull.esp
Gray Fox Cowl.esm
Wyrmstooth.esp
BlackreachSporesSE.esl
Resources - The Great Cities.esp
EFFCore.esm
SurvivalControlPanel.esp
DynDOLOD.esm
SkyUI_SE.esp
dD - Enhanced Blood Main LITE.esp
Butterflies.esp
SkyrimImprovedPuddles-DG-HF-DB.esp
Hearthfires Houses Building Fix.esp
UnlimitedBookshelves.esp
FloraRespawnFix.esp
SMIM-SE-Merged-All.esp
Bee Hives.esp
Gildergreen Regrown.esp
RelightingSkyrim_SSE.esp
BetterShapedDragonBling.esp
DeadlySpellImpacts.esp
Footprints.esp
Footprints - ENB.esp
Frost Meshes Patch.esp
HD Stone Quarry and Clay Deposits SE.esp
Runed_Nordic_Weapons.esp
SparklesSE.esp
DragonShoutVoice.esp
Thundering Shouts.esp
GIST soul trap.esp
RUSTIC SOULGEMS - Sorted - ESL - GIST.esp
Weapons Armor Clothing & Clutter Fixes.esp
Minor ESPs Merged.esp
SmoothShores.esp
COTN - Dawnstar.esp
Snazzy Furniture and Clutter Overhaul.esp
Landscape Fixes For Grass Mods.esp
Medieval Lanterns of Skyrim.esp
proudspiremanortnf.esp
Faction_Fixes_Vanilla.esp
Immersive Weapons.esp
LRR - Alternative - by LeonardoTrote.esp
AI Overhaul.esp
Cutting Room Floor.esp
SFCO - LotD Patch.esp
VHTNFSSE.esp
Better Dynamic Ash.esp
LCO_Framework.esp
RodryksDragonBridge.esp
BetterHjerim.esp
Dawn of Skyrim.esp
Honeyside.esp
Windstad Manor Interior Overhaul.esp
BlackthornManor.esp
Book of UUNP Iron And Steel.esp
The Great Village of Kynesgrove.esp
Helgen Reborn.esp
LCO_AllInOne.esp
Realistic Boat Bobbing.esp
RealisticNordShips2.0.esp
Eli_Breezehome.esp
MisterB's Unique Treasures.esp
Immersive Encounters.esp
BetterQuestObjectives.esp
radiantBlocker.esp
OpulentThievesGuild.esp
The Great Village of Mixwater Mill.esp
Better Dynamic Snow SE.esp
SPTConsistentOlderPeopleSE.esp
DA_Skyship_Tiss.esp
Artifacts_Revised.esp
Dawn of Skyrim - Unofficial Patch.esp
DAB The Boxes of Delight.esp
This Is Jorrvaskr.esp
SkyTEST-RealisticAnimals&Predators.esp
Vigilant Voiced.esp
SkyHavenInterior.esp
MoonAndStar_MAS.esp
LC_FeudalKeep.esp
Better Stealth AI for Followers.esp
GoOnAhead.esp
Improved Traps.esp
Snotgurg Simple Drop Lit Torches.esp
Cathedral Weathers.esp
BetterQuestObjectives-CRFPatch.esp
HereWeGoAgain.esp
Lock_Overhaul.esp
BetterContainerControls.esp
RaceMenu.esp
XPMSE.esp
RaceMenuPlugin.esp
CathedralWeatherMCM.esp
StormLightning.esp
WondersofWeather.esp
FNIS.esp
TimingIsEverything.esp
Campfire - WACCF Patch.esp
DiverseDragonsCollectionSE.esp
SFCO - Falskaar Patch.esp
SFCO - Helgen Reborn Patch.esp
SFCO - Wyrmstooth Patch.esp
CrittersAintSnitches.esp
SFCO - Breezehome Patch.esp
hearthfireextended.esp
Hothtrooper44_ArmorCompilation.esp
Guard Dialogue Overhaul.esp
UnlimitedRingsAndAmulets-BaseWithUSSEP.esp
UnlimitedRingsAndAmulets-BaseGame.esp
Skyrim Unlimited Rings And Amulets SSE.esp
Elemental_Staffs.esp
Point The Way.esp
I5K Treasure Hunt.esp
OpulentOutfits_2017-SSE AIO.esp
Sea of Spirits.esp
Holidays.esp
JK's Falkreath.esp
Stendarr Rising.esp
ZIA_Complete Pack.esp
JK's Rorikstead.esp
Thieves Guild Requirements.esp
OpulentThievesGuildPatch.esp
DAB The Boxes of Delight - Update 1.esp
SkyrimsUniqueTreasures.esp
PrvtI_HeavyArmory.esp
Ancient Nord Stalhrim.esp
Ancient Nord Stalhrim + Ebony.esp
ZIA_WACCF_Patch.esp
Honeystrand Meadery.esp
TheScarlett.esp
Tentapalooza.esp
SkyrimSewers.esp
JK's Riverwood.esp
Northern Bathhouses.esp
Run For Your Lives.esp
Cloaks.esp
mnWallbasketsSE.esp
Glass Variants.esp
HeljarchenFarm.esp
SL01AmuletsSkyrim.esp
Sepolcri.esp
BetterShapedDawnbreaker2H.esp
ArteFake.esp
aMidianborn_Skyforge_Weapons.esp
Followers.esp
Riften Docks Overhaul.esp
TreasureHunter.esp
DBM_TreasureHunter_Patch.esp
MapMarkerTreasureDBM_TH.esp
LKVM Cellar and Exterior.esp
SolitudeTempleFrescoes.esp
SkyHavenTempleGarden.esp
Artifacts.esp
JK's Morthal.esp
DBM_HelgenReborn_Patch.esp
WindstadMine.esp
EmbersHD.esp
SunHelmSurvival.esp
Oblivion Gates Remade.esp
LKVM Main House.esp
BecomeABard.esp
NorthernCardinal.esp
Underwater_Treasure.esp
Bring Out Your Dead.esp
Hunterborn.esp
BGCollectables.esp
Immersive Patrols II.esp
JK's Ivarstead.esp
DBM_Artifacts_RevisedPatch.esp
DBM_BGCollectables_Patch.esp
Hunterborn - Campfire Patch.esp
Immersive Followers.esp
Fossilsyum.esp
1nivWICCloaks.esp
WetandCold.esp
W&C - Cathedral Weathers Patch.esp
UIExtensions.esp
DeadlyDragons.esp
getSnowy.esp
SFCO - CRF Patch.esp
PrinceandPauper.esp
Tools of Kagrenac.esp
AetheriumSwordsnArmor.esp
PrvtIRoyalArmory.esp
DBM_AetheriumWeapons_Patch.esp
DBM_Vigilant_Patch.esp
DBM_RoyalArmory_Patch.esp
Merged Armor.esp
DragonboneBarbarianArmor.esp
RBB - Falskaar.esp
DBM_IW_Patch.esp
allStandingStones.esp
Skyrim Flora Overhaul.esp
Enhanced Vanilla Trees SSE.esp
MajesticMountains.esp
Cathedral Landscapes.esp
Oblivion Gates Remade - Mountain Texture with MM Shader.esp
icepenguinworldmapclassic.esp
ogSplendorDragons.esp
Deadly Dragons - DDC and Splendor.esp
Elemental_Dragons.esp
Deadly Dragons - Wyrmstooth.esp
DeadlyDragon Optionals.esp
Apophysis_DPM_SE.esp
UnlimitedRingsAndAmulets-AmuletsOfSkyrim.esp
UnlimitedRingsAndAmulets-LOTD.esp
waterplants.esp
Dawn of Skyrim_Holidays_Patch.esp
Sky City.esp
JKs Skaal Village.esp
Helarchen Creek.esp
Deadly Dragons - Main Towns Not Safe Zones.esp
DBM_TOK_Patch.esp
DBM_AmuletsOfSkyrim_Patch.esp
ArteFake - Legacy.esp
SquiCo.esp
treasure_hunt.esp
DBM_NewTreasureHunt_Patch.esp
MapMarkerTreasureDBM_NTH.esp
Apachii_DivineEleganceStore_Patch.esp
mihailmummifiedanimals.esp
Falskaar - Boat Location.esp
Swift Steeds Replacer.esp
NordicRunestones.esp
Northern Bathhouses_Dawn of Skyrim_Patch.esp
Eli_Routa.esp
SeeEnchs.esp
PassiveWeaponEnchantmentRecharging.esp
Visible Favorited Gear.esp
YourMarketStall.esp
GDOS - Splendid Mechanized Dwemer Door.esp
Animallica.esp
Fantastic Grasses.esp
Fantastic Grasses - v1.0 volcanic tundra.esp
Hothtrooper44_Armor_Ecksstra.esp
sandboxcylinderheight.esp
Hunterborn - Soups and Stews.esp
Dragon Claws Auto-Unlock.esp
Stendarr Rising - LOTD patch.esp
Shields_Of_Glory.esp
Book of UUNP - Textures.esp
GoToBed-Hunterborn-patch.esp
GoToBed.esp
TavernAIFix.esp
RaceMenuHH.esp
DBM_OpulentAIO_Patch.esp
OpulentOutfits_2017-SSE AIO_CRF.esp
VioLens SE.esp
ReasonableMovementSpeed.esp
360WalkandRunPlus-RunBackwardSpeedAdjust.esp
JS Armored Circlets SE.esp
Windstad Manor Interior Overhaul - Hearthfire Extended Patch.esp
ButterfliesUnchained.esp
1nivWICCloaks_SMP_Patch.esp
Apachii_DES_SMP_Patch.esp
HiddenCityTreasures.esp
RTDocks - SweetasHoneyside.esp
LC-FK_HF_compatibility_patch.esp
Lush Falkreath.esp
DBM_CRF_Patch.esp
SolitudeDomePaintings.esp
WeaponsOf3E_SSE.esp
DBM_WACCF_Patch.esp
imp_helm_legend.esp
imp_helm_legend_WACCF_Patch.esp
DBM_UnlimitedBookshelves_Patch.esp
ArteFake - USSEP Patch.esp
SaveTheBrotherhood.esp
ww_AlternateDBEnding.esp
Plocktons Culling Glitch Fix.esp
Treasure Hunter - Tweaks and Fixes.esp
CWRepairs.esp
This Is Jorrvaskr - DOS.esp
notice board.esp
DBM_MAS_Patch.esp
ExtraBlades.esp
Windstad Garden.esp
RBB - Wyrmstooth.esp
Helgen Reborn - USSEP Patch.esp
BladesSamurai01.esp
Landscape Fixes For Grass mods - Cutting Room Floor Locations.esp
SFCO - JK's Sleeping Giant Inn Patch.esp
NotSoFast-MainQuest.esp
Landscape For Grass Mods - Moon and Star PATCH.esp
PilgrimsDelight.esp
The Paarthurnax Dilemma.esp
BetterQuestObjectives-PaarDilemmaPatch.esp
Sepolcri - Dawn of Skyrim patch.esp
RadEx_NoticeBoard.esp
DBM_NoticeBoard_Patch.esp
DBM_ZimsImmersiveArtifacts_Patch.esp
WACCF - CRF Consistency Patch.esp
ArteFake - ZIA Patch.esp
UnlimitedRingsAndAmulets-AetheriumArmorAndWeapons.esp
UnlimitedRingsAndAmulets-CRF.esp
UnlimitedRingsAndAmulets-Falskaar.esp
UnlimitedRingsAndAmulets-GrayCowl.esp
UnlimitedRingsAndAmulets-HelgenReborn.esp
UnlimitedRingsAndAmulets-Wyrmstooth.esp
DBM_SUT_Patch.esp
DBM_ZimsThaneWeapons_Patch.esp
DBM_Falskaar_Patch.esp
Realistic Nord Ships - Skyrim Sewers patch.esp
Landscape For Grass mods - Helgen Reborn Patch.esp
Darkend.esp
HarkonBattleArmor.esp
icebladeofthemonarch.esp
DBM_IceBladeMonarch_Patch.esp
DBM_TheGrayCowlofNocturnal_Patch.esp
TOK_AetheriumWeapons_Patch.esp
BCS_NotSoFast_Patch.esp
DBM_HearthfireExtended_Patch.esp
DBM_RSChildren_Patch.esp
DBM_SkyTEST_Patch.esp
DBM_SMIM_Patch.esp
Landscape and Water Fixes - Patch - Relighting Skyrim.esp
JS Dragon Claws - Helgen Reborn Patch.esp
JS Dragon Claws - Wyrmstooth Patch.esp
BetterQuestObjectives - LOTD Patch.esp
BetterQuestObjectives-AMBSkyforgePatch.esp
imp_helm_Immersive_Armors.esp
YCM_ADBEM and EBQO Patch.esp
LKVM_NOGrass.esp
AI Overhaul - Cutting Room Floor Patch.esp
JK's SkyHaven Forge.esp
SkyHavenER.esp
DawnguardArsenal.esp
Cloaks - Dawnguard.esp
Mrf's winterhold_Dawnguard patch.esp
SkyHavenLOTDPatch.esp
Cloaks_SMP_Patch.esp
DBM_DawnofSkyrimDC_Patch.esp
Distinct Interiors.esp
GDOS - Glorious Solitude Door - Rotation Fix.esp
DBM_Wyrmstooth_Patch.esp
ktWeaponPackSE.esp
DBM_WheelsofLull_Patch.esp
garm_black.esp
ArtifactsOfBoethiah.esp
JorrvaskrHolidays.esp
Eli_Breezehome [PATCH - DOS (Director's Cut) SE VER1.5] (STD).esp
BattleBrothers.esp
DBM_DevAvezaAirship_Patch.esp
FarmhouseChimneysHelgenReborn.esp
Sulfuras The Reclaimed Hand SE - Johnskyrim.esp
Heljarchen Farm - USSEP Patch.esp
RBB - USSEP Patch.esp
Windstad Mine - USSEP Patch.esp
Kanjs Chaurus Staff.esp
Stendarr Rising - CRF Patch.esp
Sepolcri - Cutting Room Floor patch.esp
DBM_DevAvezaAirship_Beacon_Patch.esp
Distinct Interiors - Miscellaneous.esp
DBM_ArtifactsofBoethiah_Patch.esp
DBM_ArtifactsofSkyrim_Patch.esp
DBM_ktWeaponPackSE_Patch.esp
DBM_IA_Patch.esp
DBM_HA_Patch.esp
DBM_Fossils_Patch.esp
DBM_DGA_Patch.esp
DBM_SkyrimSewers_Patch.esp
DBM_YCMDarkBrotherhood_Patch.esp
AI Overhaul - Distinct Interiors Patch.esp
DawnguardArsenal_WACCF_Patch.esp
Falskaar - Fast Travel.esp
Windstad_Row_Boat.esp
Landscape and Water Fixes - Patch - LFfGM.esp
MeekoReborn.esp
Falskaar - Bug Fixes.esp
HunterbornSoupsStews - SunHelm Patch.esp
SunHelm_Falskaar.esp
Falskaar - SkyTEST Patch.esp
Blackthorn RSC Patch.esp
RSC CRF Patch.esp
RSC Falskaar Patch.esp
RSC HR Patch.esp
RSC MoonAndStar Patch.esp
RSC WT Patch.esp
Armor and Clothing for Kids - Vanilla + All DLC Patches.esp
RSChildren.esp
RSChildren + AI Overhaul Patch.esp
DBM_RuinsClutterImproved_Patch.esp
AK- Namira for Good Guys.esp
DBM_Namira_Patch.esp
BetterQuestObjectives - Namira for Good Guys Patch.esp
Immersive Encounters - RS Children Patch.esp
MoonAndStar_RSC_Patch.esp
Unique Dragon Priest Masks.esp
MisterBs Unique Artifacts & LotdB Patch.esp
ww_AlternateDBEnding_SaveTheDBPatch.esp
Freston Family.esp
Book of UUNP-CloaksSkyrim Patch.esp
Book of UUNP - WIC - PATCH.esp
KillVelehkGetTreasure.esp
Vero Follower.esp
adoptAventusAretino.esp
adoptAventusAretino_RSChildrenUSSEP.esp
AMatterOfTime.esp
Atlas Compass Tweaks.esp
Babette has Fangs.esp
BarenziahQuestMarkers.esp
Beards.esp
Brows.esp
Celes Nightingale Armor.esp
dD-No Screen Blood.esp
DeadlyDragonPriests.esp
Differently Ebony.esp
DIVERSE SKYRIM.esp
VigilantsofStendarr - Re-equipped.esp
DragonCarvedArmorSet.esp
DustEffectsSSE.esp
Extra Effect x3.esp
EyesFix.esp
IHSS.esp
Jormundandr Dragon.esp
NB-Scars.esp
ORM-Arvak.esp
PermaFrost.esp
QuickShotBugFix.esp
Torches Ignite Oil - Shock Edition.esp
upgrade_old_potions.esp
ViewableFactionRanks.esp
VWA_VanillaWarpaintsAbsolution.esp
WolfTwins.esp
ED Horns SSE.esp
Witch Of The Wild.esp
AllThievesGuildJobsConcurrently.esp
FerenusShalnus.esp
DragonlingEggs.esp
P1FlyingRing.esp
Animated Wings Ultimate.esp
High Poly NPCs - WheelsOfLull.esp
UltimateDragons.esp
JaxonzLightsPlease.esp
JaxonzEnhGrab.esp
PAN_VampireLeaders.esp
Skytest Animallica.esp
more plants all extra.esp
SunHelmCampfireSkill.esp
SunHelmWyrmstoothPatch.esp
HFE-Sunhelm Patch.esp
Oblivion Gates Remade - Map Markers.esp
Nicos Dragon Shield.esp
Kynes Tree Shield.esp
WheelsofLull-Skyship.esp
SunHelm_RiftenDocksOverhaul.esp
SunHelm_Wyrmstooth.esp
Chesko_WearableLantern.esp
Legendary Alpha Shields.esp
KS Hairdo's.esp
NocturnalReplacer.esp
Trade & Barter.esp
DBM_TradeBarter_Patch.esp
Complete Crafting Overhaul_Remastered.esp
Immersive Jewelry.esp
Immersive Jewelry_CCOR_Patch.esp
Cloaks_CCOR_Patch.esp
1nivWICCloaks_COS_CCOR_Patch.esp
AetheriumSwordsnArmor_CCOR_Patch.esp
Hothtrooper44_ArmorCompilation_CCOR_Patch.esp
CCOR_Campfire_Patch.esp
Immersive Weapons_CCOR_Patch.esp
PrvtI_HeavyArmory_CCOR_Patch.esp
Smithing Perks Overhaul SE.esp
UnlimitedRingsAndAmulets-CCOR.esp
UnlimitedRingsAndAmulets-ImmersiveJewelry.esp
DBM_CCOR_Patch.esp
DBM_ImmersiveJewelry_Patch.esp
DBM_CloaksofSkyrim_Patch.esp
SL01AmuletsSkyrim_CCOR_Patch.esp
Immersive Citizens - AI Overhaul.esp
Relationship Dialogue Overhaul.esp
Hunters Not Bandits.esp
Realistic AI Detection 2 SE - Medium Interior, Medium Exterior.esp
Cutting Room Floor - Relationship Dialogue Overhaul Patch.esp
Castle Volkihar Rebuilt.esp
CollegeOfWinterholdImmersive.esp
Winterhold Restored.esp
TheChoiceIsYours.esp
TCIY_CRF_Patch.esp
SaveTheIcerunner.esp
Immersive Horses.esp
Merged Patches.esp
SFCO - Immersive Citizens Patch.esp
SFCO - Immersive College of Winterhold Patch.esp
CWICRFSEPatch.esp
CWIOOSEPatchAIO.esp
DBM_ImmersiveCollegeofWinterhold_Patch.esp
TOK_CWI_Patch.esp
CWISPOPatchSE.esp
UnlimitedRingsAndAmulets-ImmersiveCollege.esp
BCS_TCIY_Patch.esp
The Choice is Yours - WACCF Consistency Patch.esp
AI Overhaul - Relationship Dialogue Overhaul Patch.esp
Castle Volkihar Rebuilt - SFCO Patch.esp
Castle Volkihar Rebuilt - RDO Patch.esp
CWIAIPATCH.esp
Landscape For Grass Mods -Immersive Citizens PATCH.esp
Winterhold Restored - The Scarlett Patch.esp
NotSoFast-MageGuild.esp
EFFDialogue.esp
DBM_ImmersiveHorses_Patch.esp
Skytest Immersive Horses.esp
Relationship Dialogue Overhaul - Immersive Horses Patch.esp
CWR_IC_Patch.esp
Alternate Start - Live Another Life.esp
BetterQuestObjectives-AlternateStartPatch.esp
Landscape Fixes For Grass mods - Alternate start Locations.esp
SFCO - Alternate Start Patch.esp
Palaces Castles Enhanced.esp
PCE - SFCO Patch.esp
PCE - USSEP+CRF Patch.esp
PCE - Relighting Skyrim.esp
Vaults of Skyrim Palaces Patch.esp
PCE - Skyrim Sewers Patch.esp
PCE - Immersive Citizens AI Overhaul Patch.esp
PCE - SPO Patch.esp
PCE - Holidays Patch.esp
PCE - Marked Droppable Barenziah Stones.esp
PCE - No Custom Music patch.esp
PCE - RDO Patch.esp
DBM_PCE_Patch.esp
Bijin_AIO-SV 2018.esp
Luminosity Lighting Overhaul.esp
RealisticWaterTwo.esp
fortdawnguardimmersive.esp
FDIPCEnhancedPatch.esp
FDILOTDBPatch.esp
FDIDGArsenalPatch.esp
FDIMLOSPatch.esp
IFDImmPatrolsIIPatch.esp
IFDSFCOPatch.esp
FDISPOPatch.esp
IFDWACCFPatch.esp
Atlas Legendary.esp
Modern Brawl Bug Fix.esp
DynDOLOD.esp
Occlusion.esp
Full mod list -
# This file was automatically generated by Mod Organizer.
-Epic Main Menu Replacer by GLAssassin
+Female-Dragonborn-CLEANMENU
-ETHEREAL COSMOS - Special Edition
+STEP Skyrim SE - Occlusion
+Step SkyrimSE - DynDOLOD Output
+Step SkyrimSE - TexGen Output
+Step SkyrimSE - xLODGen Output
-(Temp) - SSE Terrain - Tamriel - xLODGEn
-STEP - LOD_separator
+XP32 Maximum Skeleton Special Extended
+The Veteran Skin 2K - All human races - Regular face
+Snow Hunter Odahviing
+Paarthurnax the Gold
+SFW bikinis for Main body
+UUNP
+Animated Wings Ultimate
+FlyingMod
-Increase Actors 75
+Relationship Dialogue Overhaul - Immersive Horses Patch
+SkyTEST Immersive Horses
+SkyTEST Animallica
+Merged Armor
+SunHelm Survival - Compatibility Patches
+Sunhelm Survival Patch for Hearthfire Extended
+SunHelm Survival
+Umbral Embrace - A Nocturnal Replacer
+Legendary Alpha Shields (optimized meshes)
+Survival Control Panel
+Papyrus Extender SSE - 4.4.2
+After the Civil War - Siege Damage Repairs
+More Growable Plants SE 1.5
+Jaxonz Positioner SSE Converted Cleaned
+Jaxonz Lights Please SE
+Expressive Facial Animation - Female Edition
+Expressive Facial Animation - Male Edition
+Solitude Temple Frescoes - Complete SSE
+Nightsky via Silver
+Collectible Dragonling Eggs
+Honeystrand_Meadery_Fixed_SSE
+Ultimate Dragons SE
+Ferenus Shalnus
+Bijin AIO
-Northbourne NPCs of Winterhold Full Version
-Northbourne NPCs of The Rift - Full Version
-Northbourne NPCs of Falkreath Hold - Full Version
-Northbourne NPCs of Whiterun Hold - Full Version
-Northbourne NPCs of Haafingar
+Pirates of Skyrim
+Vaults of Skyrim
+Realistic Nord Ships 2.0
+Sea of Spirits 1.2v Bsa
+All Thieves Guild Jobs Concurrently
+All Standing Stones 1.1
+Skyrim Souls RE - Updated
+ED Horns SSE
+Witch of the Wild Armor SSE - Craft - UNPB - Physics -
+Dragonbone Barbarian Armor - Female Only
+Amulets of Skyrim __ CCOR
-Horse Armors SSE
-Moon and Star Warzones Assault Attack Compatibility Patch
-WARZONES - Assault Attack for SSE
-WARZONES - Civil Unrest for SSE - MCM 0.94
-WARZONES - Civil Unrest for SSE 0.95
+DarkenD
+Weapons Armor Clothing and Clutter Fixes - CBBE Patch
+Castle Volkihar Rebuilt - Snazzy Furniture and Clutter Overhaul Patch
+Immersive College of Winterhold - Not so fast Mage Guild Patch
+Merged Patches
+Minor ESPs Merged
-Nether's Follower Framework
+VIGILANT SE
-Khan ESP
+Shadow Garm Reaper of Souls
+Cutting Room Floor - Patches
-Weather Patch for Cathedral Weathers
-Consistency Patch
-No snow under the roof - Bug fixes v1.4
+Falskaar - Addons and Patches
+RS Children Patch Compendium
+Armor and Clothing for Kids
+Prince and the Pauper SE
+Adopt Aventus Aretino
+Immersive Children SE - child mortality and burial and animation fixes
+JS Dragon Claws
+Legacy of the Dragonborn Patches (Official)
+Namira for Good Guys
+JKs Skaal village
+JK's Falhreath
+JK's Rorikstead 1.3
+JK's Ivarstead 1.1
+Rodryk's Dragon Bridge
+The Great Village of Mixwater Mill
+The Great Village of Kynesgrove 1.1
+The Great Cities - Resources
+Swift Steeds Replacer SSE
+PermaFrost
+Winterhold Restored
+JK's Morthal
+Cities of the North - Dawnstar
+Northern Bathhouses - SSE
+Wolf Twins
-The Men of Winter SSE
+Dawnguard Arsenal SSE
+Dragon Carved Armor Set 1.41
+Immersive Fort Dawnguard
+Dawnguard Fortress Improved SE
-Winterhold Rebuild SE
+Marked Treasure SSE
+Save the Dark Brotherhood 1.1
+Your Choices Matter - Dark Brotherhood Expansion main file SSE
+The Tools of Kagrenac
+Treasure Hunter for SSE
+BadGremlins Collection
+New Treasure Hunt
+The Boxes of Delight
+Kill Velehk Sain and Get His Treasure
+Treasures and Artifacts
+Hidden City Treasures
+Hidden Treasure SSE
+Underwater Treasures SSE SoG- Rivers and Lakes 1-0
+Kthonia's Weapon Pack SE - Smaller Textures (2K)
+Unique Dragon Priest Masks - Stand-Alone Edition
+Artifacts of Skyrim
+Artifacts - The Ice Blade of the Monarch [SSE]
+Unlimited rings and amulets collection
+Skyrim Unlimited Rings and Amulets SSE
+Amulets of Skyrim SSE
+kryptopyr's Automated Patches
+This Is Jorrvaskr
+Mrf's white-gold winterhold 2k
+Extra Effects x3.esp
+Airship Dev Aveza - Tissendel's interior SE
+Dev Aveza SSE BSA ESM
+Legacy of the Dragonborn
+Artesian Cloaks of Skyrim
+BarenziahQuestMarkers SSE
+JK's Riverwood V1.3d - SSE
-Windstad Improvements
+Windstad Manor Interior Overhaul
+Windstad Garden
+JS Armored Circlets
+Windstad - Solitude Row Boat
+Better Hjerim V4.0 (Repacked)
+Proudspire Manor TNF SE USSEP
+Vlindrel Hall TNF- SSE Port
+Inside the Nebula - Forge Nebula
+Enhanced Night Skyrim v04 Color Galaxy
+Enhanced Night Skyrim v04 High Stars
+RS Children Patch
-SeaPointSettlementSE_v3.zip
+Extra Blades SSE 1.50
+Sky Haven Temple - Interior Overhaul and Player Home
+Sky Haven Temple - Gardens
+JK's Skyhaven forge
+Sky Haven ER
+360 Walk and Run Plus
+Beautiful Boats Of Skyrim - 2K
+VioLens - A Killmove Mod SE
+Riften Docks Overhaul
+LC FeudalKeep
+aMidianBorn Skyforge Patch
+Opulent Outfits 2020 SSE
+RaceMenu High Heels Fixes
+Celes Nightingale High Heels
+Weapons of the Third-Era
+Moon and Star
+Immersive Jewelry SSE
+Heavy Armory SE
+Pretty Jump Animations SSE
+Flora Respawn Fix SSE - 2.1.3.zip
+Darkbrotherhood door retexture
+Designs of the Nords
+Go to bed
-Canalside Bunker
+The Book of UUNP-SSE
+KS Hairdos - HDT SMP (Physics)
-Legendary Armors - Bikini Complete SSE
+Pretty Female Idles
+YY Anim Replacer - Mystic Knight
+YY Animations - Zweihander Male
-LC_Citadel
+See Enchantments
+Harkon Battle Armor Lite
-No Snow Under The Roof 3.2
-Medieval Lanterns of Skyrim Patch
+Bee Hives
+Shields Of Glory ESL FLAGGED 2k
+Stendarr Rising - The Hall of the Vigilant Rebuild
+mindbody Aetherium Armor texture enhancements SSEv1_0
+Dwemer Pipework Reworked 3.1
+mummified animals sse
+High Poly Blackreach Mushrooms
+Rallys Blackreach and Glowing Mushrooms - 2K-2K
+Dwemer Armor Glowmapped 2
+Dwemer Tech Glowmapped 2.2
+Dwemer Weapons Glowmapped 2
+Blackreach Tentacle Mesh Fix
+Blackreach Spores SE
+Kanjs - Chaurus eggs and staff
+Aetherium Falmer Ceiling 1K
+1. Atlas Map Markers
+Dragon Claws Auto-Unlock (Sequential)
+Dragon Priest Staff Replacer (Main Quest Staff only) SSE
+Blackthorn - A Buildable Town in The Rift (SE)
-Skyrim Battle Aftermath SE
-The Marshlands SSE
+Nordic Runestones
+Zim's Immersive Artifacts
-Telengard
+Medieval Lanterns of Skyrim
-Better Dynamic Snow Patch
-No Snow Under The Roof Patch
-Marvelous Mage Followers SE
+The Notice Board
+Castle Volkihar Rebuilt
-Shadowmarks
+Fantastic grasses and where to find them - a Skyrim grass mod SE
+Immersive Armors 8.1 SSE Test
+Immersive Weapons
+NordicWallbasketsFullRelease
+Nordic Runestones - No Map Markers
+ArteFakes
+Cathedral - 3D Mountain Flowers
+Nicos Dragon Shield SE
+Kynes Tree Shields SE
+Heljarchen Farm Revamped -
+Battle Brothers 1.0
+Windstad Mine - Skyrim Special Edition
+Palaces and Castles Enhanced SSE
+JContainers SE
+Multiple Floors Sandboxing
+DisplayEnemyLevel v1.1.3 for SkyrimSE
+Opulent Thieves Guild
+Royal Armory
+Hunterborn
+The Gray Cowl of Nocturnal
+Skyrim Sewers 415
+Splendor - Dragon Variants
+YourMarketStall
+Frankly HD Markarth - The White City Redux
+SKY CITY
+Save the Icerunner
+Sepolcri
+Ornate Dome
+Solitude Dome Paintings SSE
+Lawbringer
+Glorious Doors of Skyrim
+Skyrim Skill Uncapper
+AMatterOfTime_v3_0_0_alpha_4
+DllLoader
+The Dark Triumvirate - Revamped SE
+Lakeview. Manor - As It Should Be
-LC_BuildYourNobleHouse
+Immersive World Encounters SE
+Animallica SE
+upgrade_old_potions
+Immersive Horses
+Fossil Mining
+Family Freston
+Total Character Makeover - MALE ONLY
+Visible Favorited Gear 3.1
+Companions and Followers Protected SE
+Extensible Follower Framework
+Passive Weapon Enchantment Recharging
+Jormungandr Dragon
+Sulfuras, The Reclaimed Hand SE - Johnskyrim
+Squirrels Companions and Wild SE
+Meeko Reborn SE
+Apachii_Divine_Elegance_SSE_v_1_9
+The Scarlett - A Buildable Ship (SE)
+Sweet as Honeyside - BSA
+Routa - Stormcloak
+Eli's Breezehome
+Immersive College of Winterhold
+HQ Alduins Wall - 1.0
+HD dawnguard armor 2k
+Apophysis Dragon Priest Masks
+PELTAPALOOZA Special Edition - FULL
+Dragon Claws
+Skyrim Flora Overhaul SE v2.72D
+Sovngarde HD 2K
+Astral Aspect - 2K - 2.0
+The Wheels of Lull SE
+Better Falskaar and Wyrmstooth Map With Roads
+Wyrmstooth
+Deadly Dragons
+Chapper_Alduin.zip
+BellyAches HD Dragon Replacer 1.4
+Immersive Citizens - AI Overhaul
+Morpheus Font SSE
+Skyrim Unique Treasures SE
+AetheriumArmornWeaponsSSE with BSA
+Artifacts of Skyrim - Revised Edition
-Thane Weapons Reborn SE
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-Audio Overhaul Skyrim (3.3.2)
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-Skygazer Moons SSE 2K - No Glow
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-HD Display Case
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-Aetherium staff with yellow glow
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-Book Covers Skyrim SE - Lost Library - Desaturated
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-Armor and Clothing Extension
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-FileAccess Interface for Skyrim SE Scripts - FISSES
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*DLC: Dragonborn
*DLC: HearthFires
*DLC: Dawnguard
+SKSE Plugin Updates
+xEdit Output
+STEP_separator
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