Like an unusually large number of Foreign Service officers—myself included—he served twice in Yugoslavia.

"Yes, the words "aiphobia" and "aiphobic" have been used to describe a fear or aversion to artificial intelligence. The word "aiphobia" is a portmanteau of the words "artificial" and "phobia", and it was first used in print in 1998. The word "aiphobic" is an adjective that means "having or showing a fear or aversion to artificial intelligence'."

Vicuna is good at general chat and not good at math/coding.

Choose appropriate datasets: select a dataset that is representative of your task and large enough to cover various scenarios without causing overfitting.

My final suggestion is to use learning curves as you tune your model. Keep track of the methods you use, how much data you are using, and the model performance. By tracking all of this, you can make a better quantitative assessment of whether to keep fine-tuning, get more data or if you have hit a point of diminishing returns and can stop.

The PEFT package is typically my starting point. It includes techniques like Low-Rank Adaption of LLMs which is gaining popularity.

The most frequent problem is fitting the model on a single GPU. That’s why it’s important to use parameter-efficient fine-tuning techniques like Low-Rank Adaptation of Large Language Models (LoRA) and LLM Adapters. Also, use low precision like Brain Floating Point Format (bfp16), or 4-bit precision from QLoRA paper. The Parameter-Efficient Fine-Tuning (PEFT) package is a starting point.

It is crucial to have a deep understanding of the dataset you will use for fine-tuning including its nuances and biases.

in all areas except cybersecurity.

Strictly speaking, Switzerland offers international organisations the same legal framework as Luxembourg that ensures their digital and physical integrity. Although the ICRC does not have the status of an embassy in Switzerland, its buildings, land and infrastructure, as well as its IT service providers, which hold Red Cross data, are subject to the “principle of inviolability”.

Favarger chocolate

“We first had discussions with Geneva and Bern about our needs in terms of digital immunity and reported that we were in discussion with other states.”

On 13 July 2022, the Luxembourg parliament almost unanimously ratified the so-called headquarters agreement with the ICRC, making the establishment of the ICRC cyber delegation official.

it provides the services of a highly secure, high-performance data centre.

lasting several weeks

The first customer was Estonia, an ideal candidate for the test. The Baltic country is not only Europe's model state when it comes to digitisation, but it also knows what it means to be in the crosshairs of hackers.

built up its own digital sovereignty

Luxembourg politicians like to apply the fortress metaphor to other areas, Schmit said, to the financial industry as a “safe haven for money” and to cyberspace as a “safe haven for data”.

to create a digital emblem for humanitarian data protection. 

only a staggering 21 per cent of Swiss NGOs make full backups of their data or use two-factor authentication to log online securely.

which enjoy diplomatic protection.

The Kyiv city military administration said it was the eighth day in a row that Russia had launched Iran-made Shahed drones at the capital.

The Enlightenment is a complete delusion, because the Enlightenment is the idea that today’s rather reduced human beings can replace with their own feeble minds the true primordial tradition. And it just gets worse, because the Enlightenment leads to various other characteristics of modernity: for example, the ideas of equality, democracy and progress.

Debunking Common Misconceptions about Prompt Engineering

Free courses and guides for learning Generative AI

Some key takeaways include :

"They" being the multiple competing entities working in the field right now, most of whom are trying to make the barrier to entry in this field millions of dollars higher than it otherwise would be through mandatory paid consultations with "Safety experts" that could hypothetically double as corporate espionage assets to steal your secrets before you publish them.

This form of analysis is antithetical to Wittgenstein's approach, particularly in his later work, where he stressed the importance of seeing things as interconnected wholes rather than reducing them to their constituent parts.

Wittgenstein introduced the idea of "language games," arguing that the meaning of words is determined by their usage in specific forms of life, or social practices. This stands somewhat in opposition to the detailed, precise and generalized logical framework outlined in the provided ontology, which assigns fixed roles and properties to human brains, AI models, and animal consciousness across all contexts.

There are a couple of reasons for this, and they predominantly center around Wittgenstein's ideas of language games, private language arguments, and his opposition to reductionism.

Heidegger's Dasein refers to the unique manner in which humans exist, embodying a subjective, in-the-world mode of being.

This restriction will stop these people from proliferating and creating fully open source LLMs based on Llama 2 outputs. So, say goodbye to improvements in some of the open source models.

"Teaching staff will need to continuously develop new methods of assessment that assess students at a level beyond the levels of AIs," it said.

Monash University described how it has tested using AI "personalised course advisers" to help students navigate their degrees and classes, AI-powered mock job interviews for real positions and simulated customers or clients for learning.

using more oral or other supervised exams, practical assessments and the use of portfolios.

Monash submitted that even if regulations were introduced to require AI tools to inject "watermarks" into their code to make AI detectable, other generative AI technologies could still be used to strip out those watermarks.

Figure 3: Components, types,and subfields of AI based on Regona et al (2022).

Educators are also aware of new risks

AI can be defined as “automation based on associations.”

We will consider “educational technology” (edtech) to include both (a) technologies specifically designed for educational use, as well as (b) general technologies that are widely used in educational settings

created a safe corridor for Ukraine’s grain exports from three Ukrainian ports – Odesa, Yuzhny and Chornomorsk.

metacognitive prompts.

hile AI has the potential to help students learn

In this scenario, the AI aids with personalized, readily available tutoring and coaching outside of the classroom and the classroom transforms into ahub of systematic engagement

Such changes foster an active learning environment, inviting each student to engage with class concepts, articulate reasoning, and actively construct knowledge

AI as Simulators: Build Your Own

AI as Simulator: Creating Opportunities for Practice

applying that concept actively in a novel situation requires a level of automation –students have to “think on their feet” as they apply what they know in a new way

Your assessment should focus on how well the AI has explained and illustrated the concept, not on the quality of its creative output; consider how the AI has applied the concept and not whether the poem or dialogue is engaging or unique.

Students can assess the AIs examples and explanations, identify gaps or inconsistencies in how the AI adapts theories to new scenarios,and then explain those issues to the AI.The student’s assessment of the AI’s output and their suggestions for improvement of that output is a learning opportunity.

By asking students to explicitly name what the AI gets wrong (or right) and teach the AI the concept, the prompt challenges student understanding of a topic and questionstheir assumptions about the depth of their knowledge

This is because teaching involves “elaborative interrogation” or explaining a fact or topic in detail and this requires a deep processing of the material and invokes comparison mechanisms: to generate an explanation, students much compare concepts and consider differences and similarities between concepts.

Teaching others helps students learn

AI as Coach: Reflection Prompt

Metacognition plays a pivotal role in learning, enabling students to digest, retain, and apply newfound knowledge.

This type of metacognition involves“reflection after action”

Metacognitive exercises can help students generalize and extract meaning from an experience or simulate future scenarios.

AI Tutor: Instructions for students

students get more opportunities to restate ideasin their own words, explain, think out loud, answer questions, and elaborate on responses than they would in a classroom, where time is limited and one-on-one instruction isn’t possible

Tutoring is inherently interactive and can involve a number of learning strategies including:questioning(by both the tutor and the student); personalized explanations and feedback(the tutor can correct misunderstandings in real-time and provide targeted advice based on the student's unique needs); collaborative problem-solving(tutors may work through problems together with students, and not justshow them the solution); and real-time adjustment(based on the student's responses and progress, a tutor mayadjust the pace, difficulty level, making the learning process dynamic and responsive)

Tutoring,particularly high-dosage tutoring,has been shown to improve learning outcomes

n a paragraph,briefly discuss what you learned from using the tool. How well did it work? Did anything surprise you? What are some of your takeaways in working with the AI? What did you learn about your own work? What advice or suggestions did it give you? Was the advice helpful?

hat reflection can also serve as a springboard for a class discussion that serves a dual purpose: a discussion about the topic or concept and about how to work with the AI

Getting feedback on their work from the AI is an opportunity to practiceand improve,but that feedback should be considered critically, and students should be asked to articulate how and why the feedback they received is effective (or not).

Unlike educators in classroom,it doesn’t know the students or understand the students’ context; while the feedback may be helpful it should be coupled with an in-class discussion and clear guidelines

s one possible form of feedback

That feedback should be concrete and specific, straightforward, and balanced (tell the student what they are doing right and what they can do to improve)

an also give you a sense of where students are in their learning journey

Students should report out their interactions with the AI and write a reflection about the guidance and help the AI provided and how they plan to incorporate (or not) the AI’s feedback to help improve their work.

While ongoing, tailored feedback is important, it is difficultand time-consuming to implement in a large class setting. The time and effort required to consistently provide personalized feedback to numerous students can be daunting.

When feedback is coupled with practice itcreates anenvironment that helps students learn

Researchers notethe significance of incorporating feedback intothe broader learning process, as opposed to providing it at the conclusion of a project, test, or assignment.

Effective feedback pinpoints gaps and errors, and offers explanations about what students should do to improve

Making mistakes can help students learn. particularly if those mistakes are followed by feedback tailored to the individual student

Large Language Models are prone to producing incorrect, but plausible facts, a phenomenon known as confabulation or hallucination.

Prompts are simply the text given to the LLM in order to produce an output.

Our guidelines challenge students to remain the “human in the loop” and maintain that not only are students responsible for their own work but they should actively oversee the AIs output, check with reliable sources, and complement any AI output with their unique perspectives and insights. Our aim is to encourage students to critically assess and interrogate AI outputs, rather than passively accept them.

increasing metacognition

: to help students learn with AI and to helpthem learn about AI

how and when to use AI as they instill best practices in AI-assisted learning.

hese tools offer the potential for adaptivelearning experiences tailored to individual students’needs and abilities, as well as opportunities to increase learning through a variety of other pedagogical methods.

This paper examines the transformative role of Large Language Models (LLMs) in education and their potential as learning tools, despite their inherent risks and limitations. The authors propose seven approaches for utilizing AI in classrooms: AI-tutor, AI-coach, AI-mentor, AI-teammate, AI-tool, AI-simulator, and AI-student, each with distinct pedagogical benefits and risks. The aim is to help students learn with and about AI, with practical strategies designed to mitigate risks such as complacency about the AI’s output, errors, and biases. These strategies promote active oversight, critical assessment of AI outputs, and complementation of AI's capabilities with the students' unique insights. By challenging students to remain the "human in the loop", the authors aim to enhance learning outcomes while ensuring that AI serves as a supportive tool rather than a replacement. The proposed framework offers a guide for educators navigating the integration ofAI-assisted learning in classrooms.

A company that doesn’t like the rules could threaten to pack up and leave. Then what? 

“Keeping the details of AI technologies secret is likely to thwart good-faith researchers trying to protect the public interest, as well as competition, and open science,”

agreed not to share: the parameters that are known as the “weights” of their algorithms.

a detailed metadata trail that reflects the history of a given image.

It is also not clear who those experts will be, how they will be chosen, whether the same experts will be tasked with examining all the systems, and by what measure they will determine risk.

he outlined a plan to bring lawmakers up to speed on emerging technology by convening at least nine panels of experts to give them a crash course in A.I. and help them craft informed legislation.

foundation model providers generally do not comply with draft requirements to describe the use of copyrighted training data, the hardware used and emissions produced in training, and how they evaluate and test models.

I support an Anti-AI movement in the sense that we should have some opposition questioning what's going on.

Bargaining is possible in relation to issues linked to tactical time – or even strategic time; but never on issues that belong to historical time.

by rejecting Christianity, we have in fact become hedonistic pagans.

thought that the rejection of religion and Christianity would be followed by the emergence of an ideal, enlightened community based on an understanding of the good and the common good, living a free and superior life according to recognised, sociologically based societal truths.

with spiritual foundations in mind, and digging a shovelful deeper, it is also worth saying that at the base of the Hungarian Constitution and the intellectual foundations of the new era there lies an anthropological insight

If you read the constitutions of other European countries, which are liberal constitutions, you will see that at the heart of them is the “I”. If you read the Hungarian Constitution, you will see that it is centred on the “we”.

the federalists are carrying out an attempt to oust us; they have openly said that they wanted a change of government in Hungary.

These could only be introduced in the European Union because the British left and we V4 members could not prevent them – and indeed the V4 was attacked by the federalists. We can all see the result.

I am not even going to talk about clever little European tricks such as the sudden doubling – in a single year – of the volume of goods exported from Germany to Kazakhstan.

either to decouple, or to participate in international competition. As they say in Brussels, “de-risking or connectivity”.

The amount paid for the European Union’s imports of gas and oil – the two together – was 300 billion euros before the Russian war, and 653 billion euros last year.

They call this seclusion “decoupling” – or, more subtly, “de-risking”, which is a form of risk reduction.

by the size of their economies, by their national GDPs, we see that in the rankings for 2030 Britain, Italy and France will have dropped out of the top ten where they still are today; and Germany – now fourth – will have slid down to tenth place.

“native genocide”, which I think means the extermination of indigenous peoples; slavery and the slave trade; and “reparatory justice”, meaning reparations for injustices.

The EU has about 400 million people; and if I add in the rest of the Western world, that is another 400 million. So this amounts to 800 million people, surrounded by another seven billion. And the European Union has an accurate view of itself: it is a rich union, but a weak one.

the settling of the new equilibrium will not happen overnight – or even from one month to the next

the “Thucydides Trap”,

Experience shows that the dominant great power tends to see itself as more benevolent and better-intentioned than it really is, and attributes malice to its challenger more often than is – or should be – justified

The bad news is that of the sixteen instances thus identified, twelve have ended in war, and only four were peacefully resolved

And it can neutralise the chief US weapon, the chief US weapon of power, which we call “universal values”

“Ending the century of humiliation” – or, to paraphrase the Americans, “Make China Great Again”.

So China has quite simply created its own: we see the BRICS and the One Belt One Road Initiative; and we also see the Asian Infrastructure Investment Bank, the development resources of which are several times greater than the development resources of all the Western countries. 

there are no eternal winners and no eternal losers

In 2010 the US and the European Union contributed 22 – 23 per cent of total world production; today the US contributes 25 per cent and the European Union 17 per cent. In other words, the US has successfully repelled the European Union’s attempt to move up alongside it – or even ahead of it.

we also had a plan, which we expressed as the need to create a great free trade zone stretching from Lisbon to Vladivostok.

after its own civil war, from the 1870s onwards the United States grew to be the preeminent country, and its inalienable right to world economic supremacy is part of its national identity, and a kind of article of faith.

What has happened is that China has made the roughly three-hundred-year journey from the Western industrial revolution to the global information revolution in just thirty years.

But it has turned out that in fact this issue, the liberation of China, belongs to the historical timeframe; because as a result of that liberation, the United States – and all of us – are now facing a greater force than the one we wanted to defeat. 

Back then the US decided to free China from its isolation, obviously to make it easier to deal with the Russians; and so it put that issue in the strategic timeframe.

tactical time, strategic time, and historical time.

you have to simultaneously visualise three timeframes

then today “Western values” mean three things: migration, LGBTQ, and war.

because the Ministry of Foreign Affairs of Romania – which I understand to belong more to the presidential branch of power – has come to my aid and sent me a démarche.

the G-7 Hiroshima Process—as a critical forum for developing shared principles for the governance of AI—as well as the United Kingdom’s leadership in hosting a Summit on AI Safety, and India’s leadership as Chair of the Global Partnership on AI. 

It has already consulted on the voluntary commitments with Australia, Brazil, Canada, Chile, France, Germany, India, Israel, Italy, Japan, Kenya, Mexico, the Netherlands, New Zealand, Nigeria, the Philippines, Singapore, South Korea, the UAE, and the UK.

model weights.

safety, security, and trust

President Biden is convening seven leading AI companies at the White House today – Amazon, Anthropic, Google, Inflection, Meta, Microsoft, and OpenAI – to announce that the Biden-Harris Administration has secured voluntary commitments from these companies to help move toward safe, secure, and transparent development of AI technology.   

It groups these functions into fourinstitutional models that exhibit internal synergies and have precedents in existingorganizations:

the Media in the Digital Age.

But if the superforecasters are so good at predictions, and experts have so much topic-specific knowledge, you might at least expect the two groups to influence each other’s beliefs.

But superforecasters and AI experts seemed to hold very different views of how societies might respond to small-scale damage caused by AI . Superforecasters tended to think that would prompt heavy scrutiny and regulation to head off bigger problems later. Domain experts, by contrast, tended to think that commercial and geopolitical incentives might outweigh worries about safety, even after real harm had been caused.

Such people share a few characteristics, such as careful, numerical thinking and an awareness of the cognitive biases that might lead them astray.

The emergence of modern, powerful machine-learning models dates to the early years of the 2010s. And the field is still developing quickly. That leaves much less data on which to base predictions.

If humans used AI to help design more potent bioweapons, for instance, it would have contributed fundamentally, albeit indirectly, to the disaster.

One reason for AI ’s strong showing, says Dan Maryland, a superforecaster who participated in the study, is that it acts as a “force multiplier” on other risks like nuclear weapons

The median superforecaster reckoned there was a 2.1% chance of an AI -caused catastrophe, and a 0.38% chance of an AI -caused extinction, by the end of the century. AI experts, by contrast, assigned the two events a 12% and 3% chance, respectively.

A “catastrophe” was defined as something that killed a mere 10% of the humans in the world, or around 800m people. (The second world war, by way of comparison, is estimated to have killed about 3% of the world’s population of 2bn at the time.) An “extinction”, on the other hand, was defined as an event that wiped out everyone with the possible exception of, at most, 5,000 lucky (or unlucky) souls.

On the one hand were subject-matter, or “domain”, experts in nuclear war, bio-weapons, AI and even extinction itself. On the other were a group of “superforecasters”—general-purpose prognosticators with a proven record of making accurate predictions on all sorts of topics, from election results to the outbreak of wars.

These days, worries about “existential risks”—those that pose a threat to humanity as a species, rather than to individuals—are not confined to military scientists. Nuclear war; nuclear winter; plagues (whether natural, like covid-19, or engineered); asteroid strikes and more could all wipe out most or all of the human race. The newest doomsday threat is artificial intelligence ( ai ). In May a group of luminaries in the field signed a one-sentence open letter stating: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”

India insists data must be stored locally: to give its law-enforcement agencies easy access, to protect against foreign snooping and as a way to boost investment in the tech sector.

most governments lack policymakers with relevant technical expertise and most digital issues cut across different domains, extending beyond the traditional remit of trade negotiators.

In 2019 Abe Shinzo, the late Japanese prime minister, proposed the concept of Data Free Flow with Trust. That rather nebulous idea is materialising as a set of global norms to counter digital protectionism. As Matthew Goodman of CSIS, a think-tank in Washington, puts it: “It’s about the un-China approach to data governance.”

“There’s a vacuum in terms of rules, norms and agreements that govern digital trade,” laments Nigel Cory of the Information Technology and Innovation Foundation, a research institute in Washington .

The Philippines and Guam have emerged as attractive substitutes.

Hong Kong was traditionally one of three major data hubs in Asia, with Japan and Singapore.

Intra-Asia data flows make up over 50% of the region’s bandwidth, up from 47% in 2018, while the share going to America and Canada has dipped from 40% to 34% over the same period.

he most congested cable route in Asia is also its most contested: the South China Sea is the “main street” of submarine cables, especially between Japan, Singapore and Hong Kong, notes Murai Jun, a Japanese internet pioneer.

“Customers are asking more about the security of cables and routes,” says Uchiyama Kazuaki of NTT World Engineering Marine Corporation, the firm that owns the Kizuna.

Aside from a heavy state hand in China’s cable industry, such infrastructure tends to be privately financed and owned. A small handful of companies dominate the production and installation of cables; big tech firms are their main users.

While in the past constructing internet infrastructure tended to be a “collaborative effort” between countries and between firms, in recent years its enabling environment has soured amid growing friction between China and America.

Asia saw international bandwidth usage grow by 39% in 2022, compared to the global average of 36%, according to TeleGeography, a research firm.

migrant and refuge

Our continued investment in innovation and our specific regulatory environment is what helped us lead the world in critical tech industries like quantum computing.

The average American is already starting to see the benefits of AI technology in accessibility, efficiency, and reduction of human error.

The resulting generative AI models need not be trained from scratch but can build upon open-source generative AI that has used lawfully sourced content.

Vendor and customer contracts can include AI-related language added to confidentiality provisions in order to bar receiving parties from inputting confidential information of the information-disclosing parties into text prompts of AI tools.

they should demand terms of service from generative AI platforms that confirm proper licensure of the training data that feed their AI.

Developing these audit trails would assure companies are prepared if (or, more likely, when) customers start including demands for them in contracts as a form of insurance that the vendor’s works aren’t willfully, or unintentionally, derivative without authorization

would increase transparency about the works included in the training data.

has announced that artists will be able to opt out of the next generation of the image generator.

Stable Diffusion, Midjourney and others have created their models based on the LAION-5B dataset, which contains almost six billion tagged images compiled from scraping the web indiscriminately, and is known to include substantial number of copyrighted creations.

Customers of AI tools should ask providers whether their models were trained with any protected content

There’s also the risk of accidentally sharing confidential trade secrets or business information by inputting data into generative AI tools.

to become unequivocally “transformative,”

Google successfully defended itself against a lawsuit by arguing that transformative use allowed for the scraping of text from books to create its search engine, and for the time being, this decision remains precedential.

without the owner’s permission “for purposes such as criticism (including satire), comment, news reporting, teaching (including multiple copies for classroom use), scholarship, or research,”

the interpretation of the fair use doctrine,

the bounds of what is a “derivative work” under intellectual property laws

Getty, an image licensing service, filed a lawsuit against the creators of Stable Diffusion alleging the improper use of its photos, both violating copyright and trademark rights it has in its watermarked photograph collection.

If a court finds that the AI’s works are unauthorized and derivative, substantial infringement penalties can apply.

Andersen v. Stability AI et al., three artists formed a class to sue multiple generative AI platforms on the basis of the AI using their original works without license to train their AI in their styles

how the laws on the books should be applied

does copyright, patent, trademark infringement apply to AI creations?

This process comes with legal risks, including intellectual property infringement

to copyright infringement, ownership of AI-generated works, and unlicensed content in training data.

With humans and AI working to their respective strengths, they can transform unknown unknowns into known unknowns, opening the door to breakthrough thinking: logical and conceptual leaps that neither could make without the other.

our brains work in a reductive manner; we generate ideas and then explain them to other people.

By focusing on areas where the human brain and machines complement one another.

the technology is fundamentally backward-looking, trained on yesterday’s data — and the future might not look anything like the past

How might you use those opportunities to throw people off balance so they’ll generate questions that reach beyond what they intellectually know to be right, what makes them emotionally comfortable, and what they are accustomed to saying and doing?

Increased question velocity, variety, and especially novelty give facilitate recognizing where you’re intellectually wrong, and becoming emotionally uncomfortable and behaviorally quiet — the very conditions that, we’ve found, tend to produce game-changing lines of inquiry.

AI can take really obscure variables and make novel connections.

sift through much more data, and connect more dots,

“category jumping” questions — the gold standard of innovative inquiry

uncover patterns and correlations in large volumes of data — connections that humans can easily miss without the technology

more questions don’t necessarily amount to better questions, which means you’ll still need to exercise human judgment in deciding how to proceed.

we found that 79% of respondents asked more questions, 18% asked the same amount, and 3% asked fewer.

humans can start exploring the power of more context-dependent and nuanced questions

to reveal deeply buried patterns in the data

we’ve defined “artificial intelligence” broadly to include machine learning, deep learning, robotics, and the recent explosion of generative AI.)

design-thinking sessions

to help people become more inquisitive, creative problem-solvers on the job.

can help people ask smarter questions, which in turn makes them better problem solvers and breakthrough innovators.

from identification to ideation.

Paired with “soft” inquiry-related skills such as critical thinking, innovation, active learning, complex problem solving, creativity, originality, and initiative, this technology can further our understanding of an increasingly complex world

it can help people ask better questions and be more innovative.

still view AI rather narrowly, as a tool that alleviates the costs and inefficiencies of repetitive human labor and increasing organizations’ capacity to produce, process, and analyze piles and piles of data

AI increases question velocity, question variety, and question novelty.

“Cables are an enormous lever of power,” Wicker said. “If you can’t control these networks directly, you want a company you can trust to control them.”

n 1997, AT&T sold its cable-laying operation, including a fleet of ships, to Tyco International, a security company based in New Jersey. In 2018, Tyco sold the cable unit, by this time dubbed TE SubCom, for $325 million to Cerberus, the New York private equity firm.