Tuesday, May 2, 2023

Peach blossom (DE Delaware state flower): is one training #iheartradio #aiMachineLearning when one thumbs up and thumbs down a song? Thinking Yes, PLUS How to write #MachineLearning #ArtificialIntelligenceHTML (#WUaSprogramming) like #iHeartRadio ? * * * Wiki #BretonLanguage @WorldUnivAndSch in #CelticBretonLanguage in future- https://wiki.worlduniversityandschool.org/wiki/Languages & #FranceWUaS https://wiki.worlduniversityandschool.org/wiki/France planned in French in the 29 out of ~200 countries in world https://wiki.worlduniversityandschool.org/wiki/Nation_States for WUaS free #MITOCW-centric #GoogleWUaS university degrees? * * * (continuing) Ma - and friends - events around 4 corrupt? upmc 'resolve crisis' visits



How to write #MachineLearning #ArtificialIntelligenceHTML (#WUaSprogramming) like #iHeartRadio? A free #WYSIWYGwebsiteEditor #MACprogram? Helpful #KompoZer costs now? #ApacheNetBeans requires insecure Java? #GoogleBard says it writes HTML but how? Fwd to











* 

is one training #iheartradio #aiMachineLearning when one thumbs up and thumbs down a song?
Thinking yes
PLUS 
How to write #MachineLearning #ArtificialIntelligenceHTML (#WUaSprogramming) like #iHeartRadio ?












#

Does #Bard write html & how would #GoogleBard facilitate my updating my website's HTML please? (http://scottmacleod.com/ & http://worlduniversityandschool.org/) 'Yes, Bard can write HTML. I can generate HTML code from scratch, or I can edit existing HTML code. I can also generate HTML code...'




Think I'll begin with something simple - 







* 
From Google Bard - 


profile picture

Does Bard write html, and how would Bard facilitate my updating my website's HTML please?

Yes, Bard can write HTML. I can generate HTML code from scratch, or I can edit existing HTML code. I can also generate HTML code that is optimized for search engines.

To facilitate your updating your website's HTML, I can do the following:

  • Generate new HTML code for pages or sections of your website.
  • Edit existing HTML code to make changes to the content, layout, or functionality of your website.
  • Optimize your website's HTML code for search engines.
  • Help you troubleshoot any HTML errors that you may encounter.

I can also provide you with information about HTML, such as the syntax of HTML tags and attributes, the different types of HTML elements, and how to use HTML to create different types of web pages.

If you need help updating your website's HTML, please feel free to ask me. I would be happy to help you.


* * * 
How best to begin to build a machine learning large language model artificial intelligence with this World University and School wiki subject page - https://wiki.worlduniversityandschool.org/wiki/Subjects - and in many languages now, and simply?


To build a machine learning large language model artificial intelligence, you will need to follow these steps:

  1. Gather a large dataset of text and code. This dataset should be as diverse as possible, and it should cover a wide range of topics. You can find datasets online, or you can create your own by scraping websites or collecting text from books, articles, and other sources.
  2. Clean the data. Once you have gathered your dataset, you will need to clean it. This means removing any errors or inconsistencies in the data. You can use a variety of tools to clean your data, such as OpenRefine or Google Sheets.
  3. Prepare the data for training. Once your data is clean, you will need to prepare it for training. This means converting the data into a format that can be used by a machine learning algorithm. You can use a variety of tools to prepare your data, such as the TensorFlow Data API or the PyTorch DataLoader.
  4. Choose a machine learning algorithm. There are many different machine learning algorithms that can be used to train a large language model. Some of the most popular algorithms include BERT, GPT-3, and T5.
  5. Train the model. Once you have chosen a machine learning algorithm, you will need to train the model. This can take a long time, depending on the size of your dataset and the complexity of your model. You can train your model using a variety of tools, such as Google Colab or Amazon SageMaker.
  6. Evaluate the model. Once the model is trained, you will need to evaluate it. This means testing the model on a held-out dataset to see how well it performs. You can use a variety of metrics to evaluate your model, such as accuracy, precision, and recall.
  7. Deploy the model. Once the model is trained and evaluated, you can deploy it. This means making the model available to users. You can deploy your model in a variety of ways, such as through a web application or a mobile app.

Building a machine learning large language model artificial intelligence is a complex task, but it is possible with the right tools and resources. By following these steps, you can build a model that can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way.

In addition to the steps above, here are some additional tips for building a machine learning large language model artificial intelligence:

  • Use a cloud-based machine learning platform. Cloud-based platforms provide the computing power and storage space you need to train and deploy a large language model.
  • Use a pre-trained model. Pre-trained models are models that have already been trained on a large dataset. This can save you a lot of time and effort.
  • Use a transfer learning approach. Transfer learning is a technique that can be used to improve the performance of a model on a new task. This is done by using a model that has already been trained on a similar task.
  • Use a variety of data sources. The more data you have, the better your model will perform. Try to use a variety of data sources, such as books, articles, and websites.
  • Use a variety of evaluation metrics. There is no single metric that can be used to evaluate the performance of a machine learning model. Use a variety of metrics to get a better understanding of how your model is performing.
  • Monitor your model. Once your model is deployed, you will need to monitor it to make sure it is performing as expected. Monitor your model's accuracy, precision, recall, and other metrics.

* 
What does an artificial intelligence machine learning large language model do? 

An artificial intelligence machine learning large language model (LLM) is a type of artificial intelligence (AI) that is trained on a massive dataset of text and code. This allows the LLM to learn the patterns and relationships between words, and to generate text that is both coherent and grammatically accurate. LLMs can be used for a variety of tasks, including:

  • Text generation: LLMs can be used to generate text, such as news articles, blog posts, and even creative writing.
  • Translation: LLMs can be used to translate text from one language to another.
  • Question answering: LLMs can be used to answer questions about a variety of topics.
  • Summarization: LLMs can be used to summarize text, such as news articles or research papers.
  • Code generation: LLMs can be used to generate code, such as Python or Java code.

LLMs are still under development, but they have the potential to revolutionize the way we interact with computers. They can be used to create more natural and engaging user interfaces, and to automate tasks that are currently done by humans.



* 

Here are the steps on how to build a large language model machine learning with the World University and School wiki subject page and in many languages:

  1. Collect data. The first step is to collect data. This can be done by scraping the World University and School wiki subject page or by using other sources of data, such as news articles, books, or websites.
  2. Clean and preprocess the data. Once you have collected the data, you need to clean and preprocess it. This involves removing any errors or inconsistencies in the data, and converting it into a format that can be used by a machine learning model.
  3. Choose a machine learning model. There are many different machine learning models that can be used to build a large language model. Some popular models include Transformer, GPT-3, and RoBERTa.
  4. Train the model. Once you have chosen a machine learning model, you need to train it. This involves feeding the model the data that you have collected and cleaned. The model will then learn to identify patterns in the data and use these patterns to generate text.
  5. Evaluate the model. Once the model has been trained, you need to evaluate it. This involves testing the model on a set of data that it has not seen before. This will help you to determine how well the model performs on new data.
  6. Deploy the model. Once the model has been evaluated, you can deploy it. This means making the model available to users so that they can use it to generate text.

Here are some additional tips for building a large language model machine learning:

  • Use a large dataset. The more data you have, the better your model will perform.
  • Use a powerful machine. Training a large language model can be computationally expensive, so you will need a powerful machine to do it.
  • Be patient. Training a large language model can take a long time, so be patient and don't give up.




--


Scottish Small Piping album #2 - Honey Piobaireachd (2022)


- Scott GK MacLeod  
Founder, President, CEO & Professor
CC-4 licensed MIT OCW-centric. Wiki, 
World University & School (WUaS) 
- PO Box 442, Canyon, CA 94516 
- 210 East End Avenue, Pittsburgh, PA 15221
1) non-profit World University and School - http://worlduniversityandschool.org  
2) for profit general stock company WUaS Corporation in CA - http://worlduniversityandschool.org/AcademicPress.html

(m) 412 478 0116 - sgkmacleod@gmail.com 

World Univ & Sch Innovation Research -  scottmacleod.com 







* * *  


Wiki #BretonLanguage @WorldUnivAndSch in #CelticBretonLanguage in future- https://wiki.worlduniversityandschool.org/wiki/Languages & #FranceWUaS
https://wiki.worlduniversityandschool.org/wiki/France planned in French in the 29 out of ~200 countries in world
https://wiki.worlduniversityandschool.org/wiki/Nation_States for WUaS free #MITOCW-centric #GoogleWUaS university degrees?


Wiki #BretonLanguage @WorldUnivAndSch in #CelticBretonLanguage in future- https://wiki.worlduniversityandschool.org/wiki/Languages & #FranceWUaS
https://wiki.worlduniversityandschool.org/wiki/France planned in French in the 29 out of ~200 countries in world
https://wiki.worlduniversityandschool.org/wiki/Nation_States for WUaS free #MITOCW-centric #GoogleWUaS university degrees?













* * * 

(continuing) Ma - and friends - events around 4 corrupt? upmc 'resolve crisis' visits 


Sending again in this new email thread since the last email I sent from previous related email seems to have covered up the first 3/4s of this email (and please refer to the other thread too) - AND wifi hotspot from smartphone is now working and internet speed seems to have improved in the last 15 minutes (thank you Peter Norvig!) ... 

Again - 
Nick Thompson esq., (Harvard and UCLA law alumnus), Shawn Flaherty esq., (CMU and Duquesne Law alumnus), (univ pitt med ctr's David Demoise MD & Wes Sowers MD, ... and Tuft med ctr's. John Sargent MD, KP NorCal's Ed Smyth MD), All, 

Regarding corruption? in the univ pitt med ctr's 'resolve irresolvable crises" groups (i.e. potentially created by a craven psychopath? criminal f khayat?) ...

Just shared two emails with the following:  

"T-Mobile representative in East Liberty, Pgh, Kendan Jones, Peter (Norvig, a head of Google AI), lawyers Nick Thompson, Shawn Flaherty, Stanford Prof. Barbara van Schewick, Susan Davis Claus, All, 

Again - "Greetings on a Tuesday morning in asylum in PA from CA. How are you?

I don't seem to be able to access the internet at the moment, and have rebooted just now - using my new Google Pixel 6a smartphone's Hotspot ... and its wifi signal ... on MacBook Air laptop computer of 'Pixel_xxx3' via either Chrome or Safari Browsers. I recently updated my T-Mobile's unlimited video streaming data I think". ... and see email below.


... Further, Peter and Barbara, could my lack of video streaming wifi on my laptop this morning be due to the lack of cell phone towers in this neighborhood, even (as a form of redlining - and as I continue to call for the abolition of the illegal sex and drug industries internationally, and their latent networks of violence - and regarding the telecommunications' industry even too)? I noticed in searching that the American Tower Corporation on  Shiloh St. in Pgh? 

American Tower Corporation 
Website Directions Save Telecommunications service provider in Pittsburgh, Pennsylvania Address: 111 Shiloh St, Pittsburgh, PA 15211

American Tower Corporation

Telecommunications service provider in Pittsburgh, Pennsylvania

I've heard the name Shiloh multiple times, as the name of a dog on the property there, in Canyon 94516 where I lived for ~ 13 years through to September 30, 2020 (6 months into the Coronavirus pandemic), as well as said by friend and librarian Susan Davis Claus when we went to an Appalachian Square dance on February 11 (and sadly where I was sexually harassed). Could there be criminals, perpetrators, offenders, purveyors in the American Tower Corporation, and T-Mobile too? and in Google Pgh even ... all part of the illegal sex and drug industries internationally, and their latent networks of violence - as part of organized crime, and seeking to continue tragic profitable operations out of Pittsburgh PA even?

Abolition-ally, thanks, Friendly Quaker regards, 
Scott

AND 

Kendan, Peter,  (Prof. Barbara van Schewick), 

Greetings on a Tuesday morning in asylum in PA from CA. How are you?

I don't seem to be able to access the internet at the moment, and have rebooted just now - using my new Google Pixel 6a smartphone's Hotspot ... and its wifi signal on MacBook Air laptop computer of 'Pixel_xxx3' via either Chrome or Safari Browsers. I recently updated my T-Mobile's unlimited video streaming data I think.

Yesterday I was able to livestream the 5/1/23 WUaS News and Q&A - 
- AND UPLOAD this video to a WUaS Youtube channel - https://www.youtube.com/scottmacleodworlduniversity.

What do you think? What changed? What please to do? Is or could it be related to T-Mobile's non-neutrality artificial intelligence
(and see Stanford Law and CS professor and originally from Germany Barbara van Schewick's related 'net neutrality' in Europe Tweet https://twitter.com/vanschewick/status/1537046411186798598)? How please to get the video streaming I had yesterday and per the message below from Apr 24, 2023?

Seeking for federal and state of PA net neutrality laws in the US to work effectively further. 

Will reboot again. 

Thanks, abolition-ally, Friendly Quaker regards, 
Scott
Recording of Monday, 5/1/23 open World Univ & Sch WUaS News and Q&A





PS
Apr 24, 2023 
"You've used 100% of Smartphone Mobile Hotspot high speed data on your T-Mobile plan. Your Smartphone Mobile Hotspot speed will now be limited to 600 kbps until 05/15/2023. Data on your smartphone will still be at full speeds."

Thanks, abolition-ally, regards, Scott 
T-Mobile M April 24 2023 with Kendan Jones -  



2
Regarding the cyst on bottom of my left foot, just behind the ball of the foot, and my ongoing inquiry in how to reverse this, am circling around to the picture of tomatoes on FDA Commissioner Rob Califf MD's Twitter feed https://twitter.com/DrCaliff_FDA (whom I know from having met him at an UC San Francisco Med Sch talk he gave possibly 8-10 years ago) - and will now explore eliminating tomatoes from my diet and see further if cyst disappears ... 

... and see the top of Dr. Rob Califf's Twitter feed presently and regarding World Univ & Sch seeking to grow Randomized Clinical Trials RCTs for speakers of all 7151 known living languages, drawing clinical trials' samples (Ns) from all 7.9 billion people ... with packets through the mail ... 

All the best, abolition-ally, Friendly regards, Scott 


PS
Regarding RCTs and WUaS Clinical Trials  (https://wiki.worlduniversityandschool.org/wiki/Clinical_Trials_at_WUaS_(for_all_languages)) drawing Ns from 7.9 billion people - 

Again - 
"With #NEW #AgingReversal #GeneticDrugs emerging & in #ClinicalTrials #NOW & since #HumanLongevity #RCTs #WUaSclinicalTrials > #122YearsOld TAKE SO LONG @geochurch @DrCaliff_FDA #RCTs #PacketsThroughTheMail 200 #countries & langs https://wiki.worlduniversityandschool.org/wiki/Clinical_Trials_at_WUaS_(for_all_languages) Ns from 7.9 billion peops?"










Retweeting - 

Picture of FDA drug packet put into USPS PO Box from Rob Califf


The FDA is requiring manufacturers of opioid analgesics dispensed in outpatient settings to make prepaid mail-back envelopes available to outpatient pharmacies & other dispensers as an additional opioid analgesic disposal option for patients. 

Learn more: 



* 
#RCTs #PacketsThroughTheMail 200 countries & languages @WorldUnivAndSch 
"Understanding & misunderstanding #RandomizedControlledTrials" #AngusDeaton #NancyCartwright https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019115/ #WUaSClinicalTrials https://wiki.worlduniversityandschool.org/wiki/Clinical_Trials_at_WUaS_(for_all_languages) Ns from 7.9 billion people https://wiki.worlduniversityandschool.org/wiki/You_at_World_University ~










Retweeting -

Really fabulous work! Keep it up. Making the world a better place by helping generate the needed evidence for clinical, population and policy decision-making.




AND 

Very proud of what everyone has as done @DCRINews — take a look at our recent impact report where we shine the light on some stories of tackling the most vexing health problems through innovative clinical research with our partners and collaborators




AND

At DCRI, we strive to be a beacon for innovative and equitable clinical research. That’s why we’re excited to announce the release of our 2022 Impact Report. Discover some of the amazing ways we shined this past year: bddy.me/3JYK2Cg



--


Scottish Small Piping album #2 - Honey Piobaireachd (2022)


- Scott GK MacLeod  
Founder, President, CEO & Professor
CC-4 licensed MIT OCW-centric. Wiki, 
World University & School (WUaS) 
- PO Box 442, Canyon, CA 94516 
- 210 East End Avenue, Pittsburgh, PA 15221
1) non-profit World University and School - http://worlduniversityandschool.org  
2) for profit general stock company WUaS Corporation in CA - http://worlduniversityandschool.org/AcademicPress.html

(m) 412 478 0116 - sgkmacleod@gmail.com 

World Univ & Sch Innovation Research -  scottmacleod.com 




* 











https://en.wikipedia.org/wiki/Peach

https://en.wikipedia.org/wiki/Peach_Blossom_(disambiguation)

Flower[edit]

Peach flowers.jpg

The peach blossom was officially adopted on May 9, 1895

https://en.wikipedia.org/wiki/List_of_Delaware_state_symbols

...



at

No comments:

Post a Comment

Note: Only a member of this blog may post a comment.