(MENAFN- Ameliorate Digital Consultancy) The Smart Waste Bins Market report offers qualitative and quantitative insights as well as a thorough examination of the market size and expansion rate of ...

Smart Waste Bins Market Will See Strong Expansion Through 2029|Bine,Enevo,Evreka Themarketpublicist

Spot the ten places in which the right image differs from the left one. Only the right image has the clickable areas. The left image is a screen shot of Sporcle's new construction image seen during site maintenance. Picture Click: Click on regions of an ...

Diffs: Spot Ten Sporcle Construction Issues/Differences

♻️ It's time for the weekly news! Welcome back to Evreka's Sustainability Bulletin :) We will be here every Thursday with developments from around the world. Stay tuned and have a Day for a ...

Sustainability Newsletter

The smart waste management market size is expected to grow by USD 2.83 billion between 2022 and 2027. However, the growth momentum of the market will progress at a CAGR of 8.96% during the forecast period.

Smart Waste Management Market to grow by USD 2.83 billion during 2022-2027 | Increasing urbanization to drive the growth - Technavio

Whether clues are worded on a personal level (ie as if only one person fitted) or not, it is NEVER an indication of how many it applies to, but a way to shorten the clue.

Harry Potter: Good at teaching DADA Venn

Sardunya Otel is located in Bozcaada. Gestas Bozcaada Ferry Terminal and Amadeus Winery are worth checking out if an activity is on the agenda, while those wishing to experience the area's natural beauty can explore Çayır Beach and Ayazma Beach. Talay ...

Sardunya Otel

If you end up not knowing which smaller to miniature country that you haven't yet named: Look not for the green remaining country, but for the country name(s) NOT shown in the vicinity of where the country is. For example, similar to if you are missing San ...

Reveal the Countries of Asia

If you end up not knowing which smaller to miniature country that you haven't yet named: Look not for the green remaining country, but for the country name(s) NOT shown in the vicinity of where the country is. For example, similar to if you are missing ...

Reveal the Countries of Africa

Reveal the Countries of Europe

For the purpose of this quiz the Nordic countries are the five (main) countries that are considered as part of this region in this region. (Check the tags of this quiz for a list of them, if you are uncertain of which they are.) Further the quiz tests ...

North to South: Nordic countries in Order

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Movies, cartoons, and anime have long warned us about numerous realistic apocalyptic scenarios due to climate change that are just around the corner. From “Wall-E” to “Interstellar” and “Nausicaä of the Valley of the Wind”. But I’ve never paid much thought to it, that is until I’ve watched a Netflix documentary . “David Attenborough: A Life on Our Planet” Shocking details of our world melting and the planet’s ecosystem collapsing because of human actions made me acutely aware of the situation we’re in and that the next ten years are crucial for Earth. We produce more than we can consume and we’re drowning in trash. CO2 emissions are rising, the Earth is getting warmer, and the diversity of species is disappearing. It all made me wonder what can be done about it and how emerging technologies can help. So here are 5 IoT solutions that are helping save our planet right now. 1. Walmart’s ‘Eden’ Suite to Eliminate Food Waste Let’s start with food. Although the planet’s population is increasing drastically and the need for food is bigger than ever before, the topic of food waste has not vanished. Just imagine – a third of all food produced globally is annually. It is around 1.3 billion tons of food. Unless the problem of food waste is tackled, this number will grow . And to think that to produce a single food item many precious resources are spent, it is abominable to allow one-third of it to be discarded. wasted by 70 percent by 2050 Digital technology comes to the rescue. With digital capabilities, we can identify, prevent and/or reduce possible waste. One such example is an IoT solution devised by U.S. store chain Walmart that tracks the freshness of food as it moves from farms to the stores. ‘Eden’ The key indicator of food decay is changed levels of moisture in products due to higher temperature levels in container trucks. Using connected sensors, machine learning, and product tags for moisture sensing, the solution can trace food quality in real-time. So what happens if apples start to go bad on their way to some distant store? They are re-routed immediately to a closer store. Eliminating waste with this technology, Walmart aims to save over the next five years. two billion dollars 2. An eco-friendly way to grow food with vertical farming Growing enough food to feed all the planet’s population is another problem facing humanity. Despite a slow-down in population growth, the UN projects that the number of people living on Earth in 2050 will reach . According to the , 56% more food should be produced to feed everyone. 9.7 billion World Resources Institute Here’s where sustainable agriculture and farming could help. And no one does it better than innovators from Wageningen University in the Netherlands. In terms of gross value, this country constantly ranks among the , although you can drive across the whole of the Netherlands from the north to the south in less than four hours. world’s top agricultural exporters Their sustainable and well-controlled approach to vertical farming – that is growing crops on layers one above the other – does not rely on soil, sunshine, water, and pesticides. And more importantly, vertical farms do not require vast amounts of arable land, compared to conventional farming, and avoid further deforestation. IoT makes vertical farms more modular and helps monitor the health of crops that are grown. Smart greenhouses have sensors installed that gather data on temperature, humidity, pH, and CO2 levels, as well as light and water. Thanks to this real-time data farmers can intelligently monitor and control their crops, regulating temperature, humidity, lighting, spraying, irrigation, and more. 3. Evreka solution for a smart way to collect waste Now is the time to have the trash talk. Not only it is contaminating oceans and soils, producing harmful gasses, and making our planet inhabitable, but the whole process of garbage collection is far from perfect. To keep our cities clean and save the time and effort of waste management companies, IoT route optimization systems have been devised. One of them is a Turkey-based company called . Evreka This IoT management system makes dumpsters “smart” to gain information about how much they are filled. Sensors that are durable against heat and water are attached to containers. They collect information about location, temperature, and fill levels, and send it to the cloud. Later, this data is used to form the optimum route of the vehicle collecting garbage and to calculate the frequency of such visits. 4. Smart waste management system Envac to dispose of waste One Swedish waste management company has gone further than just making their garbage bins smart. They have implemented a vacuum-powered system that is my absolute favorite solution not only to dispose of waste but also to sort it for further reuse and recycling. This brilliant waste management system is called . It uses high-pressure underground tubes that suck garbage bags from the bins and transport them into a sorting center. But before making it to the tubes, the garbage bag has to be thrown in the correct container – for organic waste, recyclables, and for all other waste. Organic waste is turned into biogas and all other types of waste are used to produce electricity or heat. Envac The bins are equipped with sensors that detect when they are full. It takes 10 seconds to empty the whole bin underground so that they don’t overflow. One set of such smart waste bins can serve 30-50 families. Residents even get feedback on their smartphones about how much waste they produce and how much biogas. 5. Energy-efficient cities with Novalume's smart streetlight solution City street lights are the last thing I’d like to mention here. Despite using lots of energy and producing air pollution with CO2 emissions, city lights can have negative effects on human health. There are companies with ready-made IoT solutions that help not only save costs with LED streetlights but also reduce energy consumption and CO2 emissions by 30%. is a Danish company that delivers lighting solutions for city municipalities. Their IoT system called LUMINTELL™ optimizes street light usage to decrease energy use during off-peak traffic hours. Each street light is wirelessly connected to the online application in the cloud. Using the software solution, municipalities workers can see the entire street light installation and monitor their operations. This function reduces 75% of maintenance costs. Novalume Solutions smart city Energy-efficient solutions, solutions that help recycle waste with sensor-based technology, vertical farming, and solutions that help eliminate food waste – all these examples of IoT technology solutions are great tools in our battle to save Earth from ecological catastrophes that are looming. But the more such solutions, the better. So, now it’s up to us, humans, to use all methods available to us and act.

A Battle for Earth: 5 Ways IoT Can Help Save Our Planet

Hi! I’m Nikolai Khechumov from ’s team. This is the second part of our journey, where we are trying to improve secrets detection. , we examined different types of secrets, understood the core problems, and hit a dead end. Now we are going to make a breakthrough and do something useful. Avito Application Security In the previous part Imitating SAST Okay, since we cannot easily use the existing tools, let’s try to understand how they work and review the first two steps any SAST tool makes to build an AST. A very simplified scheme is shown below: These two steps are “lexing” and “parsing.” The Lexing (also known as ‘tokenization’) stage receives a code as just a stream of chars. Then it finds very basic language-specific syntax constructions and outputs them as a set of typed tokens — small strings with semantic interpretation. For example, a token ‘def’ is not just three chars but a keyword reserved for function declaration. We now have valuable insights about the purpose of every token, but the context itself is still missing. Python The parsing stage adds valuable context. It combines tokens into higher-level language constructions and outputs them in a form called an “abstract syntax tree.” Now we have more structural details: groups of tokens became variables, functions, and so on. For us, the question is still the same: how. Eureka! One day, while making a presentation for a talk, I had a code snippet. I wanted to format it nicely, started a browser, and typed “syntax highlighting online.” Then I opened the first link, pasted my code, pressed “highlight,” and.. a lighting strike hit somewhere near me. What I did is I found a tool that: definitely makes tokenization under the hood light enough to work inside a web browser supports dozens of languages and formats out of the box Forget about the presentation. Let’s find something similar running on Python. And yes, I found it. 538 languages supported I found , a fantastic library that solved the most significant problem: language-dependent tokenization. It still uses regexes under the hood, but those regexes are not written by me. Pygments That’s a killer feature! The library is about syntax highlighting but it features , so we can output a raw stream of tokens with their semantic meaning. RawTokenLexer Our first problem — decreasing the number of strings for analysis — is solved. Now we understand the type of every token and can just ignore useless ones: keywords, punctuation, numbers, operators, etc., leaving only literals and comments. But we are still unable to understand the names and values of variables. Variable Detection The lexing problem seems to be solved. Now let's move on to parsing. Building a true AST looks a bit redundant for our problem, so let’s optimize. Further research has shown that the type of token is more important than its value for variable detection. We need to look for . Once the pattern is found, we can make additional checks against the values of the tokens inside it. patterns inside a stream of token types to detect variables To create a Token Type Stream (TTS), I took one character from the type name of each token. Thanks to Pygments, token types are common across languages and formats. Eventually, a Variable Detection Rule (VDR) may contain the following: Reference to look inside a TTS (regex with match groups) pattern for match groups that check for expected values inside the pattern (eq. useful for finding assignment punctuation) MatchRules to clarify a group’s semantic purpose MatchSemantics Example! So let’s take our simple code snippet: def main(arg: str):
  a = 3 
  b = 'hello'
  return f'{a}{b}' Represent as an array with TTS. Basically, the variable of our interest ( ) is between the 20th and the 25th token. b The reference pattern here should be something like this: (n)t*(o|p)t*(s)(s)(s)t Let’s apply it to the TTS Match groups help us to apply additional verification logic. And finally, a rule may be supplemented with our vision of semantics. Summarizing everything The cool part here is that approach allows you to cover any language with variable detection using only 4-6 rules. New Secrets Detection Rule Semantic information about a given file enables us to analyze deeper in the right context. For example, we can now calculate entropy for a variable’s value, knowing for sure that this specific substring is a variable's value. Names of variables are also important for analysis. There are two new rules I introduced: Suspicious variable naming (low confidence) Suspicious variable naming + high entropy of a variable's value Now we can also use hashed secrets as a source of new rules. A hashed secret rule can contain information about the original secret length to improve performance. Outcomes This approach became a giant step forward for Avito: we received a noticeable performance boost (up to 60%) and +200% new findings we could not see before. Of course, the false positive rate has also grown, but it’s mostly due to test secrets. The findings are semantically correct. Limitations Plaintext files without extensions or incorrect extensions are obviously unsupported; tokenization fallbacks to the “blind mode” Variable Detection Rules (VDRs) are still a kind of compromise; they’re language-specific and may not guarantee absolute correctness (although we did not face any problem with that) We’re ready to share it with you! Our code scanning model requires every scanner to be a web service that supports our internal protocol, so we decided to extract the core functionality and open-source it as a CLI tool called DeepSecrets. You can find it here: https://github.com/avito-tech/deepsecrets Release notes are in a separate article here. Thank you! The featured image for this piece was generated with stable diffusion v2.1 Prompt: Illustrate a computer screen with the caution symbol.

Modernizing Secrets Scanning: Part 2–the Semantic Eureka

The New York “BitLicence” kills innovation and makes people less safe. We know this is a fact from the story of the incandescent light bulb The venerable has now been in many countries in the west. The reasoning behind this ban was that the bulbs are ‘inefficient’, and that removing them from use will save energy and reduce the amount of ‘carbon’ that is released into the atmosphere by the people who use them. incandescent light bulb banned As a replacement for these bulbs, ‘energy efficient’ fluorescent light bulbs were planned to completely replace the incandescent light bulb, by the force of law. All of the production lines that used to manufacture the incandescent light bulb have either been stopped or are in the process of being stopped. Capital has been diverted to the production of fluorescent light bulbs, and manufacturing capacity of the factories that make them has been increased to meet the demand caused by the ban on incandescent bulbs. The incandescent light bulb is an old technology, developed and by , and refined over many decades. They are inexpensive to manufacture, made of simple, 100% recyclable non toxic parts (glass, steel and tungsten), and there are literally of receptacles that have been designed to accommodate their shape. patented Thomas Edison billions Edison’s Light Bulbs are very simple, and 100% recyclable. The new ‘Environmentally Friendly’, ‘energy saving’ are expensive to manufacture, have plastic parts, are not simple in design and contain deadly poisons like , making it necessary to dispose of them carefully, lest the mercury escape, polluting the environment . Compact Fluorescent Light Bulbs mercury and poisoning people The new bulbs also produce a hideous, unpleasant light that flickers at the frequency of the electricity mains. These bulbs have been demonstrated to have deleterious effects on people who are sensitive to their light, causing them and . migraine headaches eye strain Just before the ban on the incandescent light bulb came into force, the following announcement of a scientific breakthrough was made: Boffins: Ordinary lightbulbs can be made efficient, cheaply Incandescents nearing extinction: Impeccable timing, everyoneBy Lewis Page Posted in Physics, 1st June 2009 11:03 GMT Just as authorities in much of the Western world have moved to phase out the incandescent lightbulb, American boffins believe they have developed a process which can make the oldschool lights more efficient than energy-saving lamps. Optics boffins at the Rochester Uni in New York state say they’ve developed a process in which an ordinary lighbulb is zapped with a femtosecond-long pulse of extremely high-energy laser light. The laser blast travels through the glass to hit the tungsten filament, causing complex nano- and micro-structures to form on its surface. Once the lasered light bulb is than powered up, according to the Rochester scientists, it emits a lot more light for the same energy compared to an untreated bulb — equivalent to 40 per cent energy savings. The process of lasing incandescent bulbs wouldn’t be expensive, apparently, so they’d remain cheap compared to fluorescent energy-saving jobs. According to Rochester Uni: The process could make a light as bright as a 100-watt bulb consume less electricity than a 60-watt bulb while remaining far cheaper and radiating a more pleasant light than a fluorescent bulb. Despite the incredible intensity involved, the femtosecond laser can be powered by a simple wall outlet, meaning that when the process is refined, implementing it to augment regular light bulbs should be relatively simple. It seems that Professor Chunlei Guo of Rochester hit upon the idea of brightening-up lightbulb filaments following earlier experiments in which he and his team used laser zapping to turn metals completely black. This worked so well that Guo and his cohorts wondered if they could reverse the process. “We fired the laser beam right through the glass of the bulb and altered a small area on the filament,” says the prof. “When we lit the bulb, we could actually see this one patch was clearly brighter than the rest of the filament, but there was no change in the bulb’s energy usage.” It seems that Guo and his team of lightbulb-blasting boffins can also produce other strange effects, getting incandescent bulbs to emit partially polarised or differently-coloured light — without the energy-wasting filters that would normally be necessary. It’s the efficiency-enhancement aspect of the studies which could make headlines, however. Both the US and European Union governments are now committed to firm timetables which will see incandescent bulbs phased out in favour of more energy-efficient alternatives, such as fluorescents. This is being done in order to save energy and so lower carbon emissions. But if it’s as simple as Guo suggests to enhance an incandescent with his laser process, this may turn out to have been an unnecessary or even retrograde step. Guo’s research has been accepted for publication by the journal Applied Physics Letters, but isn’t out yet. In the meantime, there’s a pop-sci release from the university here. http://www.theregister.co.uk/2009/06/01/light_bulb_laser_blast_enhancement/ This is a perfect example of why the State should have in what technology firms must use to produce their goods and which goods people can and cannot have access to. no say In their zeal to ‘protect the environment’ the State has diverted capital and resources away from the well established incandescent light bulb production lines, , to the new fluorescent light bulb lines, that have had their manufacturing capacity ramped up in order to meet the artificially stimulated demand for the new bad bulbs. by force The decision to ban the incandescent lightbulb was made with all of the information the legislatures had to hand; i.e. all the relevant facts about the different types of bulb that were available in 2007/2008. What they did not and could not take into account was the research in the above article, which, had they known about it, may have prevented them from legislating for the complete ban. The Knowledge Problem This is the central problem with the state interfering with technology; Now that the law is in force, we are in a situation where capital has been wasted and misdirected, resources wasted and misdirected and depending on the state of the decommissioning of the incandescent bulb lines, no costless way back to the manufacturing of incandescent light bulbs. no one can predict the future. The state, by its nature, is . They cannot predict the future and they are not omniscient. In order to be able to legislate effectively, especially where technology is concerned, they would need to be omniscient, with perfect knowledge of every piece and field of ongoing research and technology, and the of each piece and field of research and technology. incompetent potential The enormity of this amount of knowledge is beyond the capacity of any man or group of men; it would mean being able to apply each existing technology (implemented or not) and each piece of research against each other (in the case above, femtosecond lasers, metallurgy and incandescent light bulbs), considering the effect of multiples of them upon each other in succession, and then considering the knock on effects of each of these, say, ten levels down on the tree. This would produce a multi dimensional matrix or tree with a size bigger than the universe. Only then would they be able to create an optimal plan that would maximize the production and movements of capital to reach any particular goal, and of course, who has the moral authority to choose the appropriate goals is something to consider. Applying a femtosecond laser to incandescent light bulbs is one solution that has produced significant increases in efficiency. Who knows what other treatments, changes in filament formulation, the glass enclosure etc. will produce? Certainly, the state cannot possibly predict them. What the state_can_ do however, is prevent research and innovation, destroying potential breakthroughs, efficiencies, savings and progress. The state is a bumbler, a reactive and ignorant dealer; they are like a cave man being tasked to turn off a diesel engine that has been left running. Instead of getting into the car by actuating the door handle and turning the ignition key counter clockwise, the caveman takes his club out and beats against the hood covering engine until it stops running. Of course, he claims success when it stops, when in fact the tank has run out of gas and the engine cuts out of its own accord. But I digress. This process, an inexpensive, and easy addition to any incandescent light bulb production line, would have saved billions in electricity bills, spared the environment from tonnes of mercury contamination, eliminated the need to build light bulb recycling plants and spared the health of many millions of people, with all the costs attendant on that. Then you must factor in are all the other applications of this femtosecond laser technology that are now going to be delayed or which will not now come into existence. femtosecond laser Think about it; the widespread deployment of femtosecond flashers would mean designing modular systems for resale to manufacturers; out of that design and manufacturing process, other processes will have emerged. Secondary uses of these flashers would have been subsequently discovered, which would have other knock on effects. The innovation cascade resulting from this process is what the state has destroyed. When you apply this example to any other industry or technology where the state legislates, and take into account the default incompetence that inheres in the people that make these decisions, you can begin to get a glimpse of the suboptimal world that we are now in. Hovercars Imagine what sort of world it would be had the state not interfered in any way with any technology. To put it into perspective, think of the ubiquity of cheap mobile phones, and then apply that example to every expensive technology that the state has controlled in any way… like the automobile. But but but… it has no wheels! “Where we’re going, we don’t need roads” or wheels! — Back to the Future Imagine how much more efficient, inexpensive, clean and beneficial cars would be had the state stayed out of the business of the details of car manufacture. ‘Consumer advocates’ would tell you that cars are safer now only because the state intervened in the manufacturing process. This may or may not be the case, but what is certain is that cars would be had the state not interfered with the manufacture of cars. safer than they are now I do not know of a single person who would not pick a safer car over an unsafe one, and since competition is fierce in car manufacture, this fact would be taken into account at every point the design stage, producing just the sort of cars that people want, . Think iPhone here; once you see it, you want it; you did not know that you would want it before it existed, you and all of the other phone manufacturers other than Apple could not even imagine it, but now that you have seen it, you want it more than … the same could be said for the very idea of the cellular phone itself. and cars that people did not know that they wanted any other mobile phone Extrapolating from all of this, it is clear that in many aspects of the way we live, we are existing in a world that is grossly distorted and sub-optimal. This world could be better in every way by orders of magnitude had the destructive and disruptive state not interfered with the innovations and interactions of men. How this applies to Bitcoin Everything that I have written here applies to Bitcoin, and the State’s race to regulate it. They will kill Bitcoin innovation just as they did in light bulb innovation, and the long term effects will be detrimental to all mankind. Innovations like will be abandoned as unnecessary, since the State will be there as guarantor. As we all know with the bank failures and regular stock market crashes, the State is useless at regulating the economy; they will damage Bitcoin if they are allowed to touch it. Bitcoin Multisig Transactions The New York BitLicense is going to cost anyone incorporated there $2,000,000 to receive a license, and then $1,000,000 per annum to stay in business thanks to imposed “compliance” rules. None of these rules will aid a single customer or cause them to be reimbursed should something go wrong. Every company submitting to BitLicense will pass compliance costs on to their customers, making Bitcoin more expensive to use for them The companies suffering BitLicense will have two choices; leave New York entirely, or lobby for every Bitcoin company everywhere to suffer the same crippling restrictions and costs to, “level the playing field”. and only them. Leaving New York will cost far more than lobbying the State to put restrictions on all Bitcoin companies, so you can bet that this will be the preferred . If the recent efforts to pare down the BitLicence succeed, the incentive to make others comply with what BitLicence proponents believe is “reasonable” by force will be strong. They have already done the hard work, why should others get off Scott free? This is the State, pitting entrepreneur against entrepreneur. first move I have left out all the reasoning and logic that make the idea of a BitLicense a farce on stilts. You can read my pieces on . From a pure perspective of innovation being good for society and the State’s inability to protect anyone, or predict the future, any regulation of Bitcoin is a huge mistake. Light bulbs are not like Bitcoins. Bitcoin has no mass, needs no factories and do not need to be transported. They are . The people who run businesses managing that data can be anywhere, and move there instantly. They do not have to close down factories, and relocate them. They don’t even have to move computers; all they need to do is buy hosting in another, better jurisdiction. And of course, only a would start a new Bitcoin business in New York. other that subject data fool The world is changing. Business as usual is off of the table, and if jurisdictions want innovation, investment and entrepreneurs in their territories, they are going to have to adapt to this new reality, rather than fight it. You can’t fight the future. A box of clear 100w incandescent bulbs, Edison fixture ↴

The Eureka Killers

How I Created a Social Recommendation Network in Brazil

If you don’t know who Keyser Söze is and what the Eight Rules of Fight Club are, then this story ain’t for you. Buzz off! Why? Because house music is a spiritual thing and memes are a cultural thing. Memes Cultura: Movies and Sepultura https://youtu.be/AHZw09PoIU0?si=GeMg0T6NEK5gKrBx&embedable=true I remember when I watched the first Scary Movie with my daughter. We had a nice time and some good laughs. But, it just didn’t feel right. I had to do something about it. I have to be honest; it took some time to explain what parody movies are. She was a good and patient kid. I got her interested and invested in watching a bunch of movies that were parodied in Scary Movie (2000). Then, we sat down and rewatched it. I was a proud dad looking at my daughter having more than one eureka moment. Aha, this scene is from that movie, and so on. Now, it was more enjoyable and even funnier. Years later, we watched Ready Player One. I have to admit; this was next level even for me. I had to try really hard to catch up with all those comics, video games, and other movie references. Then, out of the blue, we had the most profound and spontaneous moment, I’d remember as long as I live. Daddy, can you find me a movie this scene is from? I really wanna watch it. OMG, it was no other than THE SHINING. I had tears in my eyes. I was about her age when I read the book. I never believed it’d make it to the big screen. Oh Kubrick, you genius bastard! You faked the Moon landing (allegedly) and made the movie history (undeniably). Those were the days before TikTok took her away from me and my cultural influence for good. Singularity Rhymes With Creativity Are we there yet? Nope. Until AI makes a meme all by itself, I don’t give a damn about the Turing test or the infamous CAPTCHA cheat. Look, let’s get something straight right away. The pictures of Kamala Harris in a McDonald's uniform and Donald Trump as a Warhammer 40K Space Marine are NOT legit memes, but AI-shenanigans. Lemme show you exactly what I mean. Now, that’s a legit old-school meme with a point. I’m bringing this one up because I wrote about Fiverr's Out-of-Tune Marketing Campaigns. So, this was an unexpected and a pleasant surprise. Have I tried some AI meme generators? Yes, I have. Was I happy with the results? No! I’m a fair player and a Good Karma believer. That’s why I’m not going to call out any of these companies and tools by name. I respect their efforts and hard work. They’ll get there, eventually. They just need to feed AI meme generators with more old comics and movies; and less with new features and options. Let’s wrap it up with some food for thought. If the governments (plural) go after the memes, that’s the right reason to turn on your panic mode. If AI (singular-ity) surprises you with a great meme, that’s the right reason to turn off your skeptic mode. If a picture is worth a thousand words, then memes are worth winning the elections. Let that sink in. If you don’t know who Keyser Söze is and what the Eight Rules of Fight Club are , then this story ain’t for you. Buzz off! who Keyser Söze is what the Eight Rules of Fight Club are Why? Because house music is a spiritual thing and memes are a cultural thing. house music is a spiritual thing Memes Cultura: Movies and Sepultura Memes Cultura: Movies and Sepultura https://youtu.be/AHZw09PoIU0?si=GeMg0T6NEK5gKrBx&embedable=true https://youtu.be/AHZw09PoIU0?si=GeMg0T6NEK5gKrBx&embedable=true I remember when I watched the first Scary Movie with my daughter. We had a nice time and some good laughs. But, it just didn’t feel right. I had to do something about it. I have to be honest; it took some time to explain what parody movies are. She was a good and patient kid. I got her interested and invested in watching a bunch of movies that were parodied in Scary Movie (2000). Then, we sat down and rewatched it. I was a proud dad looking at my daughter having more than one eureka moment. Aha, this scene is from that movie, and so on. Now, it was more enjoyable and even funnier. Years later, we watched Ready Player One. I have to admit; this was next level even for me. I had to try really hard to catch up with all those comics, video games, and other movie references. Then, out of the blue, we had the most profound and spontaneous moment, I’d remember as long as I live. Then, out of the blue, we had the most profound and spontaneous moment, I’d remember as long as I live. Daddy, can you find me a movie this scene is from? I really wanna watch it. OMG, it was no other than THE SHINING. I had tears in my eyes. I was about her age when I read the book. I never believed it’d make it to the big screen. Oh Kubrick, you genius bastard! You faked the Moon landing (allegedly) and made the movie history (undeniably). Those were the days before TikTok took her away from me and my cultural influence for good. Singularity Rhymes With Creativity Singularity Rhymes With Creativity Are we there yet? Nope. Until AI makes a meme all by itself, I don’t give a damn about the Turing test or the infamous CAPTCHA cheat . infamous CAPTCHA cheat Look, let’s get something straight right away. The pictures of Kamala Harris in a McDonald's uniform and Donald Trump as a Warhammer 40K Space Marine are NOT legit memes , but AI-shenanigans . Kamala Harris in a McDonald's uniform Donald Trump as a Warhammer 40K Space Marine legit memes AI-shenanigans Lemme show you exactly what I mean. Now, that’s a legit old-school meme with a point. I’m bringing this one up because I wrote about Fiverr's Out-of-Tune Marketing Campaigns . So, this was an unexpected and a pleasant surprise. Fiverr's Out-of-Tune Marketing Campaigns Have I tried some AI meme generators? Yes, I have. Was I happy with the results? No! Have I tried some AI meme generators? I’m a fair player and a Good Karma believer. That’s why I’m not going to call out any of these companies and tools by name. I respect their efforts and hard work. They’ll get there, eventually. They just need to feed AI meme generators with more old comics and movies; and less with new features and options. feed AI meme generators with more old comics and movies; and less with new features and options. Let’s wrap it up with some food for thought. If the governments (plural) go after the memes, that’s the right reason to turn on your panic mode. If AI (singular-ity) surprises you with a great meme, that’s the right reason to turn off your skeptic mode. If a picture is worth a thousand words, then memes are worth winning the elections. Let that sink in. If a picture is worth a thousand words, then memes are worth winning the elections. Let that sink in.

Can AI Make Memes?

Event Time Processing with Flink and Beam - Power of Real time Analytics

TL;DR The templating engine will give us the ability to use res.render() instead of res.send()
res.engine() will decide what res.render() will send Start Here We will create a directory which will contain our custom files inside. We will give it custom extension. In this tutorial, my extension will be "kanby". Lets create our custom files in that pages folder. Now its time to create our template engine. First we import required packages const express = require("express");
const fs = require("fs"); Then write that how you want your template engine to work app.engine('kanby', (filePath, options, callback) => { 
  fs.readFile(filePath, (err, content) => {

    // Error handler
    if (err) return callback(err)
    
    // process the content of file here
    // you can custumize however you want
    // this will change only #title# and #message#
    // but you can do advenced stuff with regular expressions. 
    // this example is the example used in express js docs
    const rendered = content.toString()
      .replace('#title#', `<title>${options.title}</title>`)
      .replace('#message#', `<h1>${options.message}</h1>`)
    return callback(null, rendered)
  })
}) After that, you need to define 2 more setting. app.set('views', './pages') // specify the directory for pages
app.set('view engine', 'kanby') // register the template engine Then you are ready ! You can use res.render() function to render your own files. app.get('/', (req, res) => {
  res.render('landingpage', { title: 'Hey', message: 'Hello there!' })
}) First it will render landingpage.kanby, the it will send rendered content to client. please do not forget to add status code res.status(200).render(); Future Plans This is basically an entrance for templating engine development. This is so simple. In my further blogs, i am thinking to create an advanced (usable) template engine for express JS. If you have any questions, Here is my Instagram @emrekanbay.en TL;DR The templating engine will give us the ability to use res.render() instead of res.send() res.engine() will decide what res.render() will send The templating engine will give us the ability to use res.render() instead of res.send() res.render() res.send() res.engine() will decide what res.render() will send res.engine() res.render() Start Here We will create a directory which will contain our custom files inside. We will give it custom extension. In this tutorial, my extension will be "kanby". Lets create our custom files in that pages folder. Now its time to create our template engine. First we import required packages First const express = require("express");
const fs = require("fs"); const express = require("express");
const fs = require("fs"); Then write that how you want your template engine to work app.engine('kanby', (filePath, options, callback) => { 
  fs.readFile(filePath, (err, content) => {

    // Error handler
    if (err) return callback(err)
    
    // process the content of file here
    // you can custumize however you want
    // this will change only #title# and #message#
    // but you can do advenced stuff with regular expressions. 
    // this example is the example used in express js docs
    const rendered = content.toString()
      .replace('#title#', `<title>${options.title}</title>`)
      .replace('#message#', `<h1>${options.message}</h1>`)
    return callback(null, rendered)
  })
}) app.engine('kanby', (filePath, options, callback) => { 
  fs.readFile(filePath, (err, content) => {

    // Error handler
    if (err) return callback(err)
    
    // process the content of file here
    // you can custumize however you want
    // this will change only #title# and #message#
    // but you can do advenced stuff with regular expressions. 
    // this example is the example used in express js docs
    const rendered = content.toString()
      .replace('#title#', `<title>${options.title}</title>`)
      .replace('#message#', `<h1>${options.message}</h1>`)
    return callback(null, rendered)
  })
}) After that, you need to define 2 more setting. app.set('views', './pages') // specify the directory for pages
app.set('view engine', 'kanby') // register the template engine app.set('views', './pages') // specify the directory for pages
app.set('view engine', 'kanby') // register the template engine Then you are ready ! You can use res.render() function to render your own files. res.render() app.get('/', (req, res) => {
  res.render('landingpage', { title: 'Hey', message: 'Hello there!' })
}) app.get('/', (req, res) => {
  res.render('landingpage', { title: 'Hey', message: 'Hello there!' })
}) First it will render landingpage.kanby, the it will send rendered content to client. please do not forget to add status code res.status(200).render(); res.status(200).render(); Future Plans This is basically an entrance for templating engine development. This is so simple. In my further blogs, i am thinking to create an advanced (usable) template engine for express JS. If you have any questions, Here is my Instagram @emrekanbay.en @emrekanbay.en

Template Engine For Express JS

This blog post is firstly published on my personal blogging site kanby.net TL;DR Most common regex patterns
Examples of regex patterns Most Common Patterns Important: a x b in this example a is preceeding by x and b is followed by x ^ means the start of each line in string
$ means the end of each line in string
() groups specific pattern
(?:) means this pattern will match in string BUT will not return it. E.g., A phone number regex pattern must include country code but does not have to extract that part even though it must match on string.
[] matches specified single character, e.g. [abc] will match a or b or c. Ranges are supported too [a-c] will match the same.
[^] matches every character except specified ones
. matches any single character
* 0 or more of the preceding element
+ 1 or more of the preceding element
? 0 or 1 of the preceding element
{n} Exactly n occurrences of the preceding element.
{n,} n or more occurrences of the preceding element.
{n,m} Between n and m occurrences of the preceding element
\d any digit
\D any non-digit
\w any word character (alphanumeric + underscore)
\W any non-word character
\s Matches any whitespace character
\S Matches any non-whitespace character
\ escape character, e.g., İf you want to find . (which is a special character) in your string, you need to do this \. By combining these, you can create highly complicated pattern match/extraction functions with Regex. Examples \^[a-z_]+\.com$\ will match .com domains


[a-z_] means characters from a to z and underscore


+ means at least one of them


\. means period (.)


com is for just com


^ and $ is for searching from the start of the string to the end of each line



^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$ will match emails ^ Asserts the start of the string.
[a-zA-Z0-9._%+-]+ Matches one or more characters that can be:

Letters (a-z, A-Z)
Digits (0-9)
Underscores (_)
Dots (.)
Percent signs (%)
Plus signs (+)
Hyphens (-)


@ Matches the "@" symbol which is mandatory in all email addresses.
[a-zA-Z0-9.-]+ Matches one or more characters for the domain name, allowing:

Letters (a-z, A-Z)
Digits (0-9)
Hyphens (-)
Dots (.)


\. Matches a literal dot (.) separating the domain name from the top-level domain (TLD).
[a-zA-Z]{2,} Matches the top-level domain (TLD) consisting of at least two letters (e.g., .com, .org).
$ Asserts the end of the string. If you have any questions, here is my Instagram @emrekanbay.en This blog post is firstly published on my personal blogging site kanby.net This blog post is firstly published on my personal blogging site kanby.net kanby.net TL;DR Most common regex patterns Examples of regex patterns Most common regex patterns Examples of regex patterns Most Common Patterns Important: a x b in this example a is preceeding by x and b is followed by x Important: a x b in this example a is preceeding by x and b is followed by x a x b a b ^ means the start of each line in string $ means the end of each line in string () groups specific pattern (?:) means this pattern will match in string BUT will not return it. E.g., A phone number regex pattern must include country code but does not have to extract that part even though it must match on string. [] matches specified single character, e.g. [abc] will match a or b or c. Ranges are supported too [a-c] will match the same. [^] matches every character except specified ones . matches any single character * 0 or more of the preceding element + 1 or more of the preceding element ? 0 or 1 of the preceding element {n} Exactly n occurrences of the preceding element. {n,} n or more occurrences of the preceding element. {n,m} Between n and m occurrences of the preceding element \d any digit \D any non-digit \w any word character (alphanumeric + underscore) \W any non-word character \s Matches any whitespace character \S Matches any non-whitespace character \ escape character, e.g., İf you want to find . (which is a special character) in your string, you need to do this \. ^ means the start of each line in string ^ $ means the end of each line in string $ () groups specific pattern () (?:) means this pattern will match in string BUT will not return it. E.g., A phone number regex pattern must include country code but does not have to extract that part even though it must match on string. (?:) [] matches specified single character, e.g. [abc] will match a or b or c. Ranges are supported too [a-c] will match the same. [] [abc] [a-c] [^] matches every character except specified ones [^] . matches any single character . * 0 or more of the preceding element * + 1 or more of the preceding element + ? 0 or 1 of the preceding element ? {n} Exactly n occurrences of the preceding element. {n} {n,} n or more occurrences of the preceding element. {n,} {n,m} Between n and m occurrences of the preceding element {n,m} \d any digit \d \D any non-digit \D \w any word character (alphanumeric + underscore) \w \W any non-word character \W \s Matches any whitespace character \s \S Matches any non-whitespace character \S \ escape character, e.g., İf you want to find . (which is a special character) in your string, you need to do this \. \ . \. By combining these, you can create highly complicated pattern match/extraction functions with Regex. Examples \^[a-z_]+\.com$\ will match .com domains


[a-z_] means characters from a to z and underscore


+ means at least one of them


\. means period (.)


com is for just com


^ and $ is for searching from the start of the string to the end of each line ^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$ will match emails \^[a-z_]+\.com$\ will match .com domains [a-z_] means characters from a to z and underscore


+ means at least one of them


\. means period (.)


com is for just com


^ and $ is for searching from the start of the string to the end of each line \^[a-z_]+\.com$\ [a-z_] means characters from a to z and underscore + means at least one of them \. means period (.) com is for just com ^ and $ is for searching from the start of the string to the end of each line [a-z_] means characters from a to z and underscore [a-z_] means characters from a to z and underscore [a-z_] + means at least one of them + means at least one of them + \. means period (.) \. means period (.) \. com is for just com com is for just com com ^ and $ is for searching from the start of the string to the end of each line ^ and $ is for searching from the start of the string to the end of each line ^ $ ^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$ will match emails ^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$ ^ Asserts the start of the string. [a-zA-Z0-9._%+-]+ Matches one or more characters that can be:

Letters (a-z, A-Z)
Digits (0-9)
Underscores (_)
Dots (.)
Percent signs (%)
Plus signs (+)
Hyphens (-) @ Matches the "@" symbol which is mandatory in all email addresses. [a-zA-Z0-9.-]+ Matches one or more characters for the domain name, allowing:

Letters (a-z, A-Z)
Digits (0-9)
Hyphens (-)
Dots (.) \. Matches a literal dot (.) separating the domain name from the top-level domain (TLD). [a-zA-Z]{2,} Matches the top-level domain (TLD) consisting of at least two letters (e.g., .com, .org). $ Asserts the end of the string. ^ Asserts the start of the string. ^ start [a-zA-Z0-9._%+-]+ Matches one or more characters that can be: Letters (a-z, A-Z)
Digits (0-9)
Underscores (_)
Dots (.)
Percent signs (%)
Plus signs (+)
Hyphens (-) [a-zA-Z0-9._%+-]+ one or more Letters (a-z, A-Z) Digits (0-9) Underscores (_) Dots (.) Percent signs (%) Plus signs (+) Hyphens (-) Letters (a-z, A-Z) Digits (0-9) Underscores (_) Dots (.) Percent signs (%) Plus signs (+) Hyphens (-) @ Matches the "@" symbol which is mandatory in all email addresses. @ "@" symbol [a-zA-Z0-9.-]+ Matches one or more characters for the domain name , allowing: Letters (a-z, A-Z)
Digits (0-9)
Hyphens (-)
Dots (.) [a-zA-Z0-9.-]+ one or more domain name Letters (a-z, A-Z) Digits (0-9) Hyphens (-) Dots (.) Letters (a-z, A-Z) Digits (0-9) Hyphens (-) Dots (.) \. Matches a literal dot (.) separating the domain name from the top-level domain (TLD). \. literal dot (.) [a-zA-Z]{2,} Matches the top-level domain (TLD) consisting of at least two letters (e.g., .com, .org). [a-zA-Z]{2,} top-level domain (TLD) two letters $ Asserts the end of the string. $ end If you have any questions, here is my Instagram @emrekanbay.en @emrekanbay.en

Regex Cheat Sheet - A Regular Expressions Guide

OpenAI just announced its newest model: ChatGPT o1. In their own words, they've trained these models to spend more time thinking through problems before they respond, much like a person would. Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes. I had no choice but to try the riddle that I used in my previous post on this new version of a reasoning model. I do not want to call it an LLM because we do not yet know much about its architecture, and it might be something different. The results were quite good. I used the same modified riddle of the farmer crossing a river that I presented last time to 4 LLM, where none of the AIs was able to resolve it successfully. Some with hilarious results, including creating new sheep to replace the one they had killed. Here is the original prompt:
A farmer wants to cross a river and take with him a wolf, a goat, and a cabbage. There is a boat that can fit him plus two ítems. If the wolf and the goat are alone on one shore, the wolf will eat the goat. If the goat and the cabbage are alone on the shore, the goat will eat the cabbage. How can the farmer bring the wolf, the goat, and the cabbage across the river? The reason the previous models were not able to solve the modified version of the riddle is that they had never seen it before. Their token-weighting system could not find in its history a proper answer. The main reason is that they could not really reason. They were like the student that has learned the material by hard and when asked for something novel it can not figure it out.
The ChatGPT o1 model was able to analyze and propose two possible solutions for this version of the riddle. Correct response To safely bring the wolf, the goat, and the cabbage across the river without any of them being eaten, the farmer can follow these steps:
Option 1: First Trip: The farmer takes the wolf and the cabbage across the river, leaving the goat alone on the original shore. This is safe because the goat won't eat anything, and there's no risk on either shore.


Second Trip: The farmer returns alone to the original shore to get the goat.


Third Trip: The farmer takes the goat across the river. Now, all three items—the wolf, the goat, and the cabbage—are safely on the other side.
At no point are the wolf and the goat left alone together, nor are the goat and the cabbage. Option 2: First Trip: The farmer takes the goat across the river, leaving the wolf and the cabbage together on the original shore. This is safe because the wolf doesn't eat cabbage.
Second Trip: The farmer returns alone to the original shore.
Third Trip: The farmer takes the wolf and the cabbage across the river.
All items are now safely on the other side. Both options ensure that none of the animals are left unsupervised in combinations where one might eat the other. By carefully planning the trips, the farmer successfully transports all three items across the river. What is new about this ChatGPT o1 model is that it will explain its reasoning. This is not only interesting to analyze but also answers the questions of LLM users who want to know how and why the model comes with an answer. Here is the reasoning process: Reasoning the mapping out of the river crossing Let’s explore the river crossing puzzle, where the boat carries the farmer and two items. The goal is to transport the wolf, goat, and cabbage without any conflicts. Ensuring policy compliance Checking for adherence to guidelines by evaluating risks and ensuring safety factors related to the user’s request. Thinking it through… I’m considering the farmer’s trips across the river. Transporting all three items in two trips wouldn’t work, as leaving the goat and cabbage together would lead to the goat eating the cabbage. Let’s explore alternatives. Weighing options I’m thinking through the farmer’s strategy, starting with the wolf and cabbage. They can be left safely together, leaving the goat behind. Working through the feasibility of making multiple trips to ensure all items are transported safely. I’m evaluating different scenarios to determine how the farmer can transport all items without any being eaten. The aim is to find the optimal solution. Charting the crossings I’m thinking through the farmer’s strategy for transporting the wolf, goat, and cabbage across the river. The sequence involves taking the wolf and cabbage together, returning for the goat, and ensuring no harm is done to any animal. Mapping out safe crossings Considering the farmer takes the goat first, then returns alone, and finally transports the wolf and cabbage, ensuring no harm happens under his watchful eye. Reassessing transportation I’m thinking through options to ferry the goat, cabbage, and wolf across the river without leaving conflicting pairs alone. Reevaluating options I’m mapping out the farmer’s journey with the goat, wolf, and cabbage. Returning alone, though, seems feasible. Progressing towards a balanced solution. Evaluating scenarios I’m working through how the farmer can successfully transfer the goat, wolf, and cabbage while keeping them safe during transport. The farmer’s presence avoids issues like the goat eating the cabbage or the wolf eating the goat. Crafting a strategy Mapping out the farmer’s crossing, the goat and cabbage can’t be left alone together with the wolf. The simplest way involves three trips: goat, then wolf, and cabbage together. Taking a closer look Interestingly enough, examining two options: transporting the goat first, then returning alone, or taking the wolf and cabbage, leaving them behind, and then returning for the goat. Both methods seem feasible. Mapping out solutions I’m detailing a logical sequence to ferry the wolf, cabbage, and goat across the river with the farmer’s assistance, ensuring no item is in danger. Ensuring safety I’m making sure each group avoids any harmful interactions. The farmer skillfully retrieves and transports each item, preventing any of them from becoming a harm to others. Analysis of the Analysis Reading the analysis feels like an interview process where you pose an interviewee a question and ask her to talk about their thinking process out loud. There are several interesting moments to consider: Understanding that there are multiple solutions. Halfway through the analysis in the section "Mapping out safe crossings," it realizes that there might be two possible answers to the question. Interestingly, as it is reassessing the options, it throws a text in Cyrillic. I was curious and got it translated to: So, it was actually trying to check with other sources. Something that we are told it still can not do. A hallucination maybe? or a preview of what a future version will be able to do? I like the way it starts on the "Taking a closer look" section. It seems to have a bit of a eureka moment when it states: "Interestingly enough: Examining two options" Creating a representation Dall-e added a fun note when asked to create a representation of the proper solution. First, it started to tell me that the solution was wrong, and it pointed me to the answer for the case known where the farmer could only take one item across. When I asked it to stop and create what I wanted, I got this: It is clear that Dall-e has not yet been augmented with the capabilities of ChatGPT o1, and it is interesting to see how it even tries to be politically correct by making the farmer's skin of different colors. How the two wolves end up in the picture is a riddle on its own. Conclusion I am positively surprised about the progress that the folks at OpenAI have made with their newer model, and I am already planning the next riddles to throw at it. Next coming up is a riddle created by the ancient Romans for the practice of Roman law... OpenAI just announced its newest model: ChatGPT o1. In their own words, they've trained these models to spend more time thinking through problems before they respond, much like a person would. Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes. I had no choice but to try the riddle that I used in my previous post on this new version of a reasoning model. I do not want to call it an LLM because we do not yet know much about its architecture, and it might be something different. The results were quite good. I used the same modified riddle of the farmer crossing a river that I presented last time to 4 LLM, where none of the AIs was able to resolve it successfully. Some with hilarious results, including creating new sheep to replace the one they had killed. Here is the original prompt:
A farmer wants to cross a river and take with him a wolf, a goat, and a cabbage. There is a boat that can fit him plus two ítems. If the wolf and the goat are alone on one shore, the wolf will eat the goat. If the goat and the cabbage are alone on the shore, the goat will eat the cabbage. How can the farmer bring the wolf, the goat, and the cabbage across the river? Here is the original prompt:
A farmer wants to cross a river and take with him a wolf, a goat, and a cabbage. There is a boat that can fit him plus two ítems. If the wolf and the goat are alone on one shore, the wolf will eat the goat. If the goat and the cabbage are alone on the shore, the goat will eat the cabbage. How can the farmer bring the wolf, the goat, and the cabbage across the river? The reason the previous models were not able to solve the modified version of the riddle is that they had never seen it before. Their token-weighting system could not find in its history a proper answer. The main reason is that they could not really reason. They were like the student that has learned the material by hard and when asked for something novel it can not figure it out.
The ChatGPT o1 model was able to analyze and propose two possible solutions for this version of the riddle. Correct response To safely bring the wolf, the goat, and the cabbage across the river without any of them being eaten, the farmer can follow these steps: Option 1: Option 1: First Trip: The farmer takes the wolf and the cabbage across the river, leaving the goat alone on the original shore. This is safe because the goat won't eat anything, and there's no risk on either shore. Second Trip: The farmer returns alone to the original shore to get the goat. Third Trip: The farmer takes the goat across the river. Now, all three items—the wolf, the goat, and the cabbage—are safely on the other side.
At no point are the wolf and the goat left alone together, nor are the goat and the cabbage. First Trip: The farmer takes the wolf and the cabbage across the river, leaving the goat alone on the original shore. This is safe because the goat won't eat anything, and there's no risk on either shore. First Trip: The farmer takes the wolf and the cabbage across the river, leaving the goat alone on the original shore. This is safe because the goat won't eat anything, and there's no risk on either shore. Second Trip: The farmer returns alone to the original shore to get the goat. Second Trip: The farmer returns alone to the original shore to get the goat. Third Trip: The farmer takes the goat across the river. Now, all three items—the wolf, the goat, and the cabbage—are safely on the other side.
At no point are the wolf and the goat left alone together, nor are the goat and the cabbage. Third Trip: The farmer takes the goat across the river. Now, all three items—the wolf, the goat, and the cabbage—are safely on the other side.
At no point are the wolf and the goat left alone together, nor are the goat and the cabbage. Option 2: Option 2: First Trip: The farmer takes the goat across the river, leaving the wolf and the cabbage together on the original shore. This is safe because the wolf doesn't eat cabbage. Second Trip: The farmer returns alone to the original shore. Third Trip: The farmer takes the wolf and the cabbage across the river.
All items are now safely on the other side. Both options ensure that none of the animals are left unsupervised in combinations where one might eat the other. By carefully planning the trips, the farmer successfully transports all three items across the river. First Trip: The farmer takes the goat across the river, leaving the wolf and the cabbage together on the original shore. This is safe because the wolf doesn't eat cabbage. Second Trip: The farmer returns alone to the original shore. Third Trip: The farmer takes the wolf and the cabbage across the river.
All items are now safely on the other side. Both options ensure that none of the animals are left unsupervised in combinations where one might eat the other. By carefully planning the trips, the farmer successfully transports all three items across the river. What is new about this ChatGPT o1 model is that it will explain its reasoning. This is not only interesting to analyze but also answers the questions of LLM users who want to know how and why the model comes with an answer. Here is the reasoning process: Reasoning the mapping out of the river crossing Let’s explore the river crossing puzzle, where the boat carries the farmer and two items. The goal is to transport the wolf, goat, and cabbage without any conflicts. Reasoning the mapping out of the river crossing Ensuring policy compliance Checking for adherence to guidelines by evaluating risks and ensuring safety factors related to the user’s request. Ensuring policy compliance Thinking it through… I’m considering the farmer’s trips across the river. Transporting all three items in two trips wouldn’t work, as leaving the goat and cabbage together would lead to the goat eating the cabbage. Let’s explore alternatives. Thinking it through… Weighing options I’m thinking through the farmer’s strategy, starting with the wolf and cabbage. They can be left safely together, leaving the goat behind. Working through the feasibility of making multiple trips to ensure all items are transported safely. I’m evaluating different scenarios to determine how the farmer can transport all items without any being eaten. The aim is to find the optimal solution. Weighing options Charting the crossings I’m thinking through the farmer’s strategy for transporting the wolf, goat, and cabbage across the river. The sequence involves taking the wolf and cabbage together, returning for the goat, and ensuring no harm is done to any animal. Charting the crossings Mapping out safe crossings Considering the farmer takes the goat first, then returns alone, and finally transports the wolf and cabbage, ensuring no harm happens under his watchful eye. Mapping out safe crossings Reassessing transportation I’m thinking through options to ferry the goat, cabbage, and wolf across the river without leaving conflicting pairs alone. Reassessing transportation Reevaluating options I’m mapping out the farmer’s journey with the goat, wolf, and cabbage. Returning alone, though, seems feasible. Progressing towards a balanced solution. Reevaluating options Evaluating scenarios I’m working through how the farmer can successfully transfer the goat, wolf, and cabbage while keeping them safe during transport. The farmer’s presence avoids issues like the goat eating the cabbage or the wolf eating the goat. Evaluating scenarios Crafting a strategy Mapping out the farmer’s crossing, the goat and cabbage can’t be left alone together with the wolf. The simplest way involves three trips: goat, then wolf, and cabbage together. Crafting a strategy Taking a closer look Interestingly enough, examining two options: transporting the goat first, then returning alone, or taking the wolf and cabbage, leaving them behind, and then returning for the goat. Both methods seem feasible. Taking a closer look Mapping out solutions I’m detailing a logical sequence to ferry the wolf, cabbage, and goat across the river with the farmer’s assistance, ensuring no item is in danger. Mapping out solutions Ensuring safety I’m making sure each group avoids any harmful interactions. The farmer skillfully retrieves and transports each item, preventing any of them from becoming a harm to others. Ensuring safety Analysis of the Analysis Reading the analysis feels like an interview process where you pose an interviewee a question and ask her to talk about their thinking process out loud. There are several interesting moments to consider: Understanding that there are multiple solutions. Halfway through the analysis in the section "Mapping out safe crossings," it realizes that there might be two possible answers to the question. Understanding that there are multiple solutions. Interestingly, as it is reassessing the options, it throws a text in Cyrillic. I was curious and got it translated to: So, it was actually trying to check with other sources. Something that we are told it still can not do. A hallucination maybe? or a preview of what a future version will be able to do? I like the way it starts on the "Taking a closer look" section. It seems to have a bit of a eureka moment when it states: "Interestingly enough: Examining two options" Creating a representation Dall-e added a fun note when asked to create a representation of the proper solution. First, it started to tell me that the solution was wrong, and it pointed me to the answer for the case known where the farmer could only take one item across. When I asked it to stop and create what I wanted, I got this: It is clear that Dall-e has not yet been augmented with the capabilities of ChatGPT o1, and it is interesting to see how it even tries to be politically correct by making the farmer's skin of different colors. How the two wolves end up in the picture is a riddle on its own. Conclusion I am positively surprised about the progress that the folks at OpenAI have made with their newer model, and I am already planning the next riddles to throw at it. Next coming up is a riddle created by the ancient Romans for the practice of Roman law...

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