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ML (machine learning) is an approach to solving difficult computational problems instead of coding using a programming language you build an algorithm that learns the solution from data samples.

AI (artificial intelligence) is a field of computer science dealing with problems (e.g., image classification, working with human language) that are difficult to solve using traditional programming. ML and AI go hand in hand, with ML being a tool to solve problems formulated in AI.

AGI (artificial general intelligence) - is the correct term for what popular culture usually implies by AI the ability of computers to achieve human-like intellectual capabilities and broad reasoning. It is still the holy grail for researchers working in the AI field.

An artificial neural network (ANN) is a class of ML algorithms and data structures (or models for short) so called because it was inspired by the structure of biological neural tissue. But this doesnt completely mimic all the biological mechanisms behind it. Rather, ANNs are complicated mathematical functions that are based on ideas from living species biology.

Neural networks are layered structures consisting of uniform units interconnected with each other in a network. The way these units are interconnected is called architecture. Each connection has an associated number called weight and the weights store information the model learns from data. So, when you read the model has 2 billion parameters, it means that there are 2 billion connections (and weights) in the model, and it roughly designates the information capacity of the neural network.

Neural networks have been studied since the 1980s but made a real impact when the computer games industry introduced cheap personal supercomputers known as graphical processing units (GPUs). Researchers adapted this hardware for the neural network training process and achieved impressive results. One of the first deep learning architectures, the convolutional neural network (CNN), was able to carry out sophisticated image recognition that was difficult with classical computer vision algorithms. Since then, ML with neural networks has been rebranded as deep learning, with deep referring to the complicated NN architectures the networks are able to explore.

Id recommend videos by Grant Sanderson available on his animated math channel.

To work with human language using computers, language must be defined mathematically. This approach should be sufficiently generic to include the distinctive features of every language. In 2003 researchers discovered how to represent language with neural networks and called it the neural probabilistic language model or LM for short. This works like predictive text in a mobile phone given some initial sequence of words (or tokens), the model can predict the next possible words with their respective probabilities. Continuing this process using previously generated words as input (this is autoregression) the model can generate text in the language for which it was trained.

Representing sequences of items was a challenging problem for neural networks. There were several attempts to solve the problem (mostly around variations of recurrent neural networks), which yielded some important ideas (e.g., word embedding, encoder-decoder architecture, and attention mechanism). In 2017 a group of Google researchers proposed a new NN architecture that they called a transformer. It combined all these ideas with effective practical implementation. It was designed to solve the language translation problem (hence the name) but proved to be efficient for capturing the statistical properties of any sequence data.

OpenAI experimented with transformers to build a neural probabilistic language model. The results of their experiments are called GPT (generative pre-trained transformer) models. Pre-trained means they were training the transformer NN on a large body of texts mined on the Internet and then taking its decoder part for language representation and text generation. There were several generations of GPTs:

Given the enormous number of parameters GPT models have (in fact, you need a huge computational cluster with hundreds to thousands of GPUs to train and serve these models), they were called Large Language Models (LLMs).

The original GPT-3 is still a word prediction engine and thus is mostly of interest to AI researchers and computational linguists. Given some initial seed or prompt, it can generate text infinitely, which makes little practical sense. The OpenAI team continued to experiment with the model, trying to fine-tune it to treat prompts as instructions to execute. They fed in a large dataset of human-curated dialogues and invented a new approach (RLHF reinforcement learning from human feedback) to significantly speed up this process with another neural network as a validator agent (typical in AI research). They released a model called InstructGPT as an MVP based on a smaller GPT-3 version and in November 2022 released a full-featured version called ChatGPT. With its simple chatbot and web UI, it changed the IT world.

Given that LLMs are just sophisticated statistical machines, the generation process could go in an unexpected and unpleasant direction. This type of result is sometimes called an AI hallucination, but from the algorithmic perspective, it is still valid, though unexpected, by human users.

Raw LLMs require treatment and additional fine-tuning with human validators and RLHF, as previously mentioned. This is to align LLMs with human expectations, and not surprisingly the process itself is called alignment. This is a long and tedious procedure with considerable human work involved; this could be considered LLM quality assurance. The alignment of the models is what distinguishes OpenAI/Microsoft ChatGPT and GPT-4 from their open-source counterparts.

Neural networks are black boxes (a huge array of numbers with some structure on top). There are some methods to explore and debug their internals but the exceptional generalization qualities of GPTs remain unexplained. This is the main reason behind the ban movement some researchers think we are playing with fire (science fiction gives us fascinating scenarios of AGI birth and technological singularity) before we get a better understanding of the processes underlying LLMs.

The most popular include:

GPTs are the most mature models with API access provided by OpenAI and Microsoft Azure OpenAI services (if you need a private subscription). But this is the frontier of AI and many interesting things have happened since the release of ChatGPT. Google has built its PaLM-2 model; Meta open-sourced their LLaMA models for researchers, which spurred lots of tweaks and enhancements (e.g., Alpaca from Stanford) and optimization (now you can run LLMs on your laptop and even smartphone).

Huggingface provides BLOOM and StarCoder and HuggingChat which are completely open source, without the LLaMA research-only limitation. Databricks trained their own completely open-source Dolly model. Lmsys.org is offering its own Vicuna LLM. Nvidias deep learning research team is developing its Megatron-LM model. The GPT4All initiative is also worth mentioning.

However, all these open-source alternatives are still behind OpenAIs major tech (especially in the alignment perspective) but the gap is rapidly closing.

The easiest way is to use OpenAI public service or their platform API playground, which offers lower-level access to the models and more control over network inner workings (specify system context, tune generation parameters, etc). But you should carefully review their service agreements since they use user interactions for additional model improvements and training. Alternatively, you can choose Microsoft Azure OpenAI services, which provide the same API and tools but with private model instances.

If you are more adventurous, you can try LLM models hosted by HuggingFace, but youll need to be more skilled with Python and data science tooling. Denis Shipilov is experienced Solutions Architect with wide range of expertise from distributed systems design to the BigData and Data Science related projects.

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Your Ultimate Guide to Chat GPT and Other Abbreviations - KDnuggets

Generative AI will have a profound impact across industries.

Thats what Amazon Web Services (AWS) believes, according to Hussein Shel, an Energy Enterprise Technologist for the company, who said Amazon has invested heavily in the development and deployment of artificial intelligence and machine learning for more than two decades for both customer-facing services and internal operations.

We are now going to see the next wave of widespread adoption of machine learning, with the opportunity for every customer experience and application to be reinvented with generative AI, including the energy industry, Shel told Rigzone.

AWS will help drive this next wave by making it easy, practical, and cost-effective for customers to use generative AI in their business across all the three layers of the technology stack, including infrastructure, machine learning tools, and purpose-built AI services, he added.

Looking at some of the applications and benefits of generative AI in the energy industry, Shel outlined that AWS sees the technology playing a pivotal role in increasing operational efficiencies, reducing health and safety exposure, enhancing customer experience, minimizing the emissions associated with energy production, and accelerating the energy transition.

For example, generative AI could play a pivotal role in addressing operational site safety, Shel said.

Energy operations often occur in remote, and sometimes hazardous and risky environments. The industry has long-sought solutions that help to reduce trips to the field, which directly correlates to reduced worker health and safety exposure, he added.

Generative AI can help the industry make significant strides towards this goal. Images from cameras stationed at field locations can be sent to a generative AI application that could scan for potential safety risks, such as faulty valves resulting in gas leaks, he continued.

Shel said the application could generate recommendations for personal protective equipment and tools and equipment for remedial work, highlighting that this would help to eliminate an initial trip to the field to identify issues, minimize operational downtime, and also reduce health and safety exposure.

Another example is reservoir modeling, Shel noted.

Generative AI models can be used for reservoir modeling by generating synthetic reservoir models that can simulate reservoir behavior, he added.

GANs are a popular generative AI technique used to generate synthetic reservoir models. The generator network of the GAN is trained to produce synthetic reservoir models that are similar to real-world reservoirs, while the discriminator network is trained to distinguish between real and synthetic reservoir models, he went on to state.

Once the generative model is trained, it can be used to generate a large number of synthetic reservoir models that can be used for reservoir simulation and optimization, reducing uncertainty and improving hydrocarbon production forecasting, Shel stated.

These reservoir models can also be used for other energy applications where subsurface understanding is critical, such as geothermal and carbon capture and storage, Shel said.

Highlighting a third example, Shel pointed out a generative AI based digital assistant.

Data access is a continuous challenge the energy industry is looking to overcome, especially considering much of its data is decades old and sits in various systems and formats, he said.

Oil and gas companies, for example, have decades of documents created throughout the subsurface workflow in different formats, i.e., PDFs, presentations, reports, memos, well logs, word documents, and finding useful information takes a considerable amount of time, he added.

According to one of the top five operators, engineers spend 60 percent of their time searching for information. Ingesting all of those documents on a generative AI based solution augmented by an index can dramatically improve data access, which can lead to making better decisions faster, Shel continued.

When asked if the thought all oil and gas companies will use generative AI in some way in the future, Shel said he did, but added that its important to stress that its still early days when it comes to defining the potential impact of generative AI on the energy industry.

At AWS, our goal is to democratize the use of generative AI, Shel told Rigzone.

To do this, were providing our customers and partners with the flexibility to choose the way they want to build with generative AI, such as building their own foundation models with purpose-built machine learning infrastructure; leveraging pre-trained foundation models as base models to build their applications; or use services with built-in generative AI without requiring any specific expertise in foundation models, he added.

Were also providing cost-efficient infrastructure and the correct security controls to help simplify deployment, he continued.

The AWS representative outlined that AI applied through machine learning will be one of the most transformational technologies of our generation, tackling some of humanitys most challenging problems, augmenting human performance, and maximizing productivity.

As such, responsible use of these technologies is key to fostering continued innovation, Shel outlined.

AWS took part in the Society of Petroleum Engineers (SPE) International Gulf Coast Sections recent Data Science Convention event in Houston, Texas, which was attended by Rigzones President. The event, which is described as the annual flagship event of the SPE-GCS Data Analytics Study Group, hosted representatives from the energy and technology sectors.

Last month, in a statement sent to Rigzone, GlobalData noted that machine learning has the potential to transform the oil and gas industry.

Machine learning is a rapidly growing field in the oil and gas industry, GlobalData said in the statement.

Overall, machine learning has the potential to improve efficiency, increase production, and reduce costs in the oil and gas industry, the company added.

In a report on machine learning in oil and gas published back in May, GlobalData highlighted several key players, including BP, ExxonMobil, Gazprom, Petronas, Rosneft, Saudi Aramco, Shell, and TotalEnergies.

Speaking to Rigzone earlier this month, Andy Wang, the Founder and Chief Executive Officer of data solutions company Prescient, said data science is the future of oil and gas.

Wang highlighted that data sciences includes many data tools, including machine learning, which he noted will be an important part of the future of the sector. When asked if he thought more and more oil companies would adopt data science, and machine learning, Wang responded positively on both counts.

Back in November 2022, OpenAI, which describes itself as an AI research and deployment company whose mission is to ensure that artificial general intelligence benefits all of humanity, introduced ChatGPT. In a statement posted on its website on November 30 last year, OpenAI said ChatGPT is a sibling model toInstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response.

In April this year, Rigzone looked at how ChatGPT will affect oil and gas jobs. To view that article, click here.

To contact the author, emailandreas.exarheas@rigzone.com

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Generative AI Will Have Profound Impact Across Sectors - Rigzone News

Generative artificial intelligence (AI) has put AI in the hands of people, and those who dont use it could struggle to keep their jobs in future, Jaspreet Bindra, Founder and MD, Tech Whisperer Lt. UK, surmised at the Mint Digital Innovation Summit on June 9.

We never think about electricity until its not there. Thats how AI used to be. It was always in the background and we never thought about it. With generative AI it has come into our hands, and 200-300 million of us are like, wow! said Bindra.

He noted that while AI wont replace humans at their jobs, someone using AI very well could. He urged working professionals to recalibrate and embrace generative AI as a powerful tool created by humans, instead of looking at it as a threat.

There is a new kid in town, who can do a bunch of things that we can too, he said, adding that humans will just be able to do tasks better and will hence have to take advantage of their own ingenuity. 60% of jobs will be impacted, not as jobs themselves but as tasks, he said.

To be sure, Bindra said that he believes generative AI to be a transformative technology, just like Search or the Internet were. He said that the technology will also reshape big tech firms themselves. The reshaping of big tech has already started, and theres a new trillion-dollar boy in town called Nvidia. Youre going to see some shaping and reshaping of the apex of technology as we go forward.

However, he also acknowledged that Generative AI (GAI) is not the same as Artificial General Intelligence (AGI) a fear that many have expressed ever since ChatGPT became popular last year.

I believe that one day AI will become more intelligent than human beings in certain aspects. What I dont believe is that itll ever get conscious or sentient. We dont understand our own brain, or our own consciousness its the hard problem in philosophy - how can we build something that will be conscious?

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Mint DIS 2023 | AI won't replace you, someone using AI will ... - TechCircle

Colorado's Libertarian Party has agreed with state Republicans to stay out of competitive races in next year's election where a right-leaning, third-party candidate could be a spoiler, the chairs of both parties announced Tuesday.

Colorado GOP Chairman Dave Williams said the agreement he negotiated with Hannah Goodman, his Libertarian counterpart, will boost the chances of Republicans winning crucial 2024 legislative and congressional races.

Williams said in a statement that he hopes the unprecedented move will "ensure that these races are not spoiled by a third-party candidate so that together we can break the stranglehold radical Democrats have over our state."

Said Goodman, in a letter addressed to Williams released by the Colorado GOP:"We would prefer to work with you, and not against you, to support the Colorado that your voters believe they are supporting. We are committed to working with you to end their one-party rule here in Colorado."

Williams told Colorado Politics that the agreement will only affect what he described as competitive races, where a Libertarian candidate's votes might make a difference.

Republicans in Colorado have long complained that Libertarian nominees siphon off votes from GOP candidates, sometimes allowing Democratic nominees to win with a plurality. Libertarians, however, have also long maintained that their candidates aren't spoilers and caution Republicans against counting on the votes their nominees receive.

The Libertarian Party is the largest of Colorado's officially recognized minor political parties, with 39,830 active, registered members as of June 1. Although the party's members account for just 1% of the state's 3.8 million registered, its nominees routinely garner 2-3% of the vote, enough to swing the results in tight races.

Williams cited Democrat Yadira Caraveo's 0.7 percentage point win last year over Republican Barb Kirkmeyer in Colorado's new 8th Congressional District, where Libertarian nominee Richard Ward took nearly 4% of the vote far more than Caraveo's razor-thin margin.

Democrats swept the ballot in Colorado last year, winning every statewide race and five of the eight congressional seats while increasing the party's majorities in both chambers of the General Assembly.

"We must seek new opportunities to build coalitions that will help restore balance back to Colorado, and this new partnership is a critical first step if we are going to win in 2024," Williams said.

In the letter, Goodman outlined the agreement, which requires that Republican nominees pass a loosely defined test involving a commitment to "liberty."

"We are calling upon the Republican Party to take our goals and objectives into serious consideration and run strong liberty minded, anti-establishment candidates going forward," Goodman wrote. "If the Republican Party runs candidates who support individual liberties, we will not run competing candidates in those races."

Added Goodman: "Furthermore, we reserve the right to run our candidates if you choose not to put forth strong liberty candidates."

Williams acknowledged that Republicans can't count on the Libertarians standing down in targeted races if the party nominates just anyone.

"They are not looking for the perfect candidate, but they are making clear that our party needs more nominees who will fight for limited-government in Denver and Washington D.C.," he said in an email to supporters.

He elaborated on how possible scenarios might play out in a text message to Colorado Politics.

"At a minimum, the Libertarians will make it known to Colorado Republicans if a primary candidate is acceptable or not," Williams said. "For example, if Joe ODea runs in CD8, they will object and make it known that they prefer their own nominee in the general election."

O'Dea, the GOP's unsuccessful 2022 U.S. Senate nominee, has been floated as a potential challenger to Caraveo, though he doesn't live in the district. In last year's election, numerous leading Republicans, including former state Rep. Ron Hanks, who lost the primary to O'Dea, withheld their support from the Republican nominee over his positions on abortion and other issues.

Williams told Colorado Politics that he forwarded the agreement to the National Republican Congressional Committee and minority leaders in the state House and Senate. He added that the state GOP "will also act as a liaison" with the groups to "express the Libertarian Partys thoughts on the field of candidates.

Democratic Gov. Jared Polis, who routinely describes himself as small-l libertarian-leaning, mocked the announcement in a Twitter post.

"And if you run more pro-liberty candidates who support a womans right to choose, the freedom to marry who you love, reducing the income tax, private property rights to build housing on your own land, and legal cannabis and psilocybin small businesses then maybe you can start calling your nominees Democrats," Polis wrote.

Dick Wadhams, a Republican poltiical consultant and former state GOP chairman, told Colorado Politics he applauded Williams for having the discussion but was skeptical about any long-term benefits the agreement might yield.

"The Libertarian chairwoman said they will not oppose Republicans who support individual liberties, but that's a pretty broad definition," Wadhams said. "You never know where they're going to come down on any issues. They'reall over the map on various issues."

Wadhamsadded that Williams might not be the best arbiter of what constitutes a goodRepublican who deserves a shot without a third-party spoiler.

"After watching Williams attack people like Congressman Doug Lamborn and former Colorado Springs Mayor John Suthers in the last couple weeks, count me as somewhat leery about him deciding on his own that a Republican candidate does not support individual liberties," Wadhams said.

"It's nice he's spending time on this, but it doesn't go to what really ails the Colorado Republican Party, which is Donald Trump and people who refuse to acknowledgethe cold hard reality that Donald Trump has defined the last four election cycles in Colorado for Colorado Republicans."

Colorado Democrat Party Chairman Shad Murib dismissed the pact between his Republican and Libertarian counterparts in a text message to Colorado Politics.

"The Colorado Republican Partys problem is not Libertarians spoiling elections for them their problem is that their platform is opposed by the vast majority of Colorado voters," Murib said. "If their path to victory is to embrace folks who are even more extreme than them, Id remind them that two wrongs dont make a right."

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Colorado Libertarians ink pact with state Republicans to stand down next year in crucial races - coloradopolitics.com

ANKARA

President Recep Tayyip Erdoan has expressed his desire to liberate Trkiye from its current constitution, which he claims is a remnant of a coup dtat, and underlined the need for a civilian, libertarian and inclusive constitution that will be embraced by all segments of Turkish society.

We, together, want to liberate our country from its current constitution, which is the product of a coup dtat. We want our journey in the second century of our republic to be guided by a civilian, libertarian and inclusive constitution that is embraced by all segments of the society, Erdoan said in his address following the cabinet meeting at the presidential complex on June 14.

The president acknowledged the results of the May elections, stating that the introduction of the presidential system of government will bring numerous benefits in the coming years.

According to Erdoan, the elections have placed Trkiye in a new league, creating a political atmosphere conducive to achieving a civilian constitution. He highlighted the strength of Turkish democracy, stating that the nation is now capable of removing the remaining shackles that hinder progress.

The president called for unity and collaboration with the ruling Peoples Alliance to draft a new constitution that reflects the aspirations of all Turkish citizens. The new vision guided by a civilian, libertarian and inclusive constitution aims to lead Trkiye into its second century with confidence and progress, he said.

He pledged to accelerate progress towards national goals, realize long-held dreams more quickly, implement projects and plans within shorter timeframes, overcome challenges and setbacks more easily and increase services that resonate with citizens.

Erdoan also emphasized a more determined fight against both domestic and international terrorist organizations, a bolder defense of Trkiyes rights on the global stage, and a stronger commitment to regional peace and stability. He reiterated his dedication to democracy, rights and freedoms, aiming to elevate the country to the level of contemporary civilizations.

Trkiye is expanding area of influence beyond its borders, the president said, noting that the recent elections garnered significant attention worldwide.

He also highlighted the admiration and affection millions of people have for the country, with many envisioning their future connected to the nation.

Erdoan expressed satisfaction with the support and interest shown during his inauguration and subsequent foreign visits.

Turkey,

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Erdoan calls for civilian, libertarian constitution - Trkiye News - Hurriyet Daily News