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‘Personal’ … The Tragedies by Emma Talbot. Photograph Courtesy the artist (The Guardian)
It’s open until the 5th of October, so you’ve plenty of time to get yourself down to How We Learn To Love. The latest Emma Talbot exhibition is at Compton Verney in Warwickshire. (It’s pronounced Warrick). She’s recently completed a residency in Italy, which she received after winning the Max Mara Prize in 2019. Now living between Emilia and the UK, Emma Talbot is exploring silk paintings with a Medean twist. She wants to portray the Greek mother Medea who killed her sons and draw comparisons to people who send soldiers to war. If a mother sends her sons to war, is she any different to Medea? Is certain death and risk of death the same thing? What if you know your sons will be doing the killing. How do you feel about that?
Browse flight discounts Utilising the flowing and lustrous quality of silk, Emma Talbot paints her images in vivid colour with beautifully designed details. Uncovering the mental anguish and existential dread that grows from thoughts of war, terror, death, and pain, the weeping and screaming of those left behind can only represent the narrative of the beaten. What a tragedy. When the UK Government is considering conscription to boost its military strength, do they realise what effect this will have on the way parents up and down the country will feel about them? I don’t think they do. It’s a good job we can vote every five years. What Emma Talbot is asking for, is perhaps a world where aggression and killing isn’t accepted anywhere. Maybe the only reason we use it ourselves it because others are already on that platform. Look at Tibet, the pacifist nation under occupation. The notion of putting your life on the line to protect something you value is not uncommon, getting used to the idea of death is the first step. In a self-centred society where the individual is marketed for and praised, who can blame anyone for never looking in that direction? These people who come from places where life is not so certain and where negative emotions compound over generations, how do we deal with the inevitable outcome? It’s not that Talbot is war obsessed, she is an emotional creator who delves deep into her own inner landscape with thoughts and feelings manifesting in her art. It’s not just silk, either, she works on animation and sculpture as well as painting in various forms. The reach of her vision stretches into pain points and difficulties that touch most modern folk and probably played a role in the distant past, too. The collection called Magical Thinking looks at how we tell stories about the facts we encounter in the world and turn our lives into a semi fairytale by embellishing on the cues. Like a little game, it can have rules and agendas that completely step out of the real world. Putting away the childish things requires us to recognise them, and perhaps this work helps us to do just that. Don’t forget, you can get to see Emma Talbot’s work, How We Learn To Love at Warwickshire’s Compton Varney until the 5th of October. Via The Guardian 
Whether you want to sell more paintings or have more people agree with your moral message, it’s a good idea to learn marketing. This isn’t a capitalist thing where you sell out for the green. Not at all. It’s about your job interview with the world, as yourself. When you apply for a job, you put your best foot forward. If you’re really serious, you do some homework and find out about the business you’re applying for. Getting your art and your communication out into the world is achieved to the best possible level when we follow the same principle. So, what actually are the benefits of this term? Are we talking about little piggies and roast beef?
One of the big issue principles of marketing is strategy. You have a goal, to sell paintings, books, ideas, or whatever. Whether you’re in political activism or a punk band or you’ve created your own rich and diverse universe across ten unique and fascinating novels, if the wide world doesn’t see the benefits of giving you a shot, what’s the point? By focusing your efforts in a way that means people sit up and listen and then remember fondly the things you’ve given them, they will often come back for more. It’s not a straight-forward method, different products, different audiences, different ideas all need their own kind of voice and social identity. Getting to this is a paramount milestone when growing your arts brand. It used to be about paper advertising and maybe ones on the radio. TV advertising is for the wealthy and still is, but now there’s social media. We all can run ads and have people see our offering. Even when we don’t pay for views, which many of us would rather not do, we can still use the social media system to organically reach a lot more than we would by handing out leaflets in town or putting on a local ad in the paper. Learning how to phrase, position, and apply advertising is key to allowing others to fully appreciate the value and scope of what you are offering. It’s vital that you learn how it works. What about this audience? Who are you aiming for? Are you likely to win over many of that statistic with that particular image or phrase? Do you need to think again? Understanding the people you are influencing is as important as finding the right message. If you’ve got a bus load of rugby players, you can’t get far with cricket metaphors. Confuse them even more by talking about something completely non-sporting, like cloud formations over Peru, and you’ll lose them bus and its driver. Speaking in terms that people understand and staying in the circle they listen to requires a persistent effort to understand their principles, their understanding of the world, and the things they value. We must learn to spend their currency. This all boils down to one simple principle, that reaches into every factor or marketing. Branding is the symbolic image that people associate with everything you stand for. Your story, your people, your imagery, and your products all fit into the one symbol or the one name that you chose to represent yourself with. The more focused and together this image becomes, the stronger your brand will be in the eyes of the customer. It’s about trust, accountability, and safety. People want to know that if they buy your idea that they won’t get in trouble later on. They want to associate with something that speaks positively about themselves, not negatively. This means that your brand is like a child who needs constant attention. The best way to build a brand that people can identify with is by using real human storytelling to instill a sense of shared vision. When you and the customer are on the same page then people are more likely to take what you’re offering. By having the right story, the right blend of motives, and the right passion, customers will be attracted to the sense of fit they get when they think about the big picture. If they fit in somewhere, they’ll feel comfortable around your offerings. This stuff isn’t easy to learn, it has to be understood, practiced, applied, and relearned several times before you become really good at it. Thankfully, YouTube is stocked full of free to watch lecture series on marketing for you to plough through. A range of sources from various lecturers are listed here so sift through the bulk and find something that resonates with your own journey. Marketing Basics by Professor Myles Bassell Introduction To Marketing by Alanys Business Academy Principles of Marketing by Kotler and Armstrong Marketing Managment by Dharmendra Gupta Principles of Marketing and Management by Bharath Naik L Marketing by Harvard Business Principles of Marketing by Virtual University of Pakistan Digital Marketing by Edureka “Best marketing lectures ever” Marketing Research and Analysis by Prof. J.K. Nayak Strategic Sales Management by IIT Roorkee Social Media Marketing by Simplilearn International Marketing by Windows of Wisdom Enjoy at your own pace, gain some wisdom, and share this list with your people so we can all get a bit more out of life. Good luck! 
As we have seen in recent modern times, AI has grown from humble party tricks like playing cards to diagnosing serious disease from images of strangers. It can create all kinds of things that we define as art, although many people question the art it makes. When we’ve seen films that involve computer soldiers and malevolent robots and read stories about computer programs going rogue and killing off the crew, we are naturally afraid. It’s what we’ve been exposed to and given licence to think via the seeding of fears and anxieties. We’ve also seen clever devices like talking cars and helpful androids, navigation computers that know everything, and digital playmates who teach foreign language and mathematics on the side. We don’t fear these things; we generally want them. This is why a lot of our modern AI is attempting to become these things.
There is a clear and obvious ethical problem at hand in that we can’t make sure that individual people or organisations use AI technology to do things we generally do not want it to do. It’s accepted as fact that military uses are numerous, with data driven warfare becoming a real phenomenon. Does this prevent unnecessary risk or relegate rich human lives to numbers in a mathematical problem? When we use AI to decide what to do with large numbers of individuals, do we risk losing the definition of society in the old sense by creating artificial frameworks based on previous experience and learning? What if someone asks the AI to design a weapon that is so far undefendable? With all forms of law frameworks and crime, it’s not possible to prevent each instance all over the world. Every nation has its own laws and methods that they are entrusted to enforce. Other nations can’t write laws for each other without international organisations that have some level of sovereignty in terms of political decision making, such as the European Union. The most powerful use of AI for good is in the science and engineering field. With the level of detail an AI can apply to any idea or plan, the system can run through any number of possible combinations and outcomes which it evaluates and then produces a result that fits the best. Generative equations create answers that are not in the database, but they use the database to provide an answer that matches those that do. This means that the output is always new, but it follows any number of patterns that means it fits. It is purely mathematical at its core, with outputs on the computer represented by numbers. In art programs, the numbers represent pixels and their colour. An image with a million pixels on a machine capable of producing a million colours will have a million factorial possible combinations. It simply choses the ones that match the pattern the best. The pixels can become human cells in an organ or weather systems in the sky, given the right amount of information and ability. At the sharp end of the cutting edge of artificial intelligence, we find the science of artificial creative invention. There are three main types of inventiveness that machines are programmed to achieve. The first type, and the one that was the first to be created by computer scientists, is interpolation. Interpolation is the ability to be given a few inputs and create a new output that considers of these inputs and creates some form of average. This average is a novel output, and not one created from the inputs, but it is created because of them. It is a matter of putting the inputs into a numerical form that is represented in as complete way as possible and then giving the system the correct functions to use this data in a way that is meaningful to its original context. The context therefore must be added to the variable information in the database, meaning that one piece of human information might have a dozen or more associated information pieces in the database that allows the AI to understand it completely. Knowing how it works, it may come as no surprise that computer scientists work with neural scientists to learn how biological minds function as information processing systems. They try to replicate the way nature uses individual neurons as transmitters of information as various chemical signals resulting in various amounts of electronic interaction. By studying the way a tiny brain in a fruit fly works, the process of nature’s mechanics can be placed in a computer system via a series of code and instructions. Translating the neural network of an insect into the functions of a working computer system is entirely dependent on what you are achieving and how the fly's basic functions can be adapted numerically to fit an entirely new model of action. It’s interesting because a fly is instinctive and it can often be predictable, it uses a very basic information system when compared to a higher ape like us, or even a cat or a dog. The level up from interpolation is extrapolation. When machines can extrapolate, they are able to create something new from the inputs that does not necessarily fit into the original database. It doesn’t use a system of averages and line of best fit, rather it predicts what would be the case in a scenario where this new information was already in the database. It can hypothesise and out the most plausible response without already being aware of what that might be. This is a lot harder. It’s like instead of making a fruit salad by chopping up the fruit you have, it’s planting a seed, waiting for the tree, and building a boat. That’s another level of intelligence. The database of information the system draws on is another level of magnitude bigger and it can plan several steps ahead. These modern art programs such as Nightcafe and Imagine Art do this well, however the real steel is in the medical and science fields where the AI can detect things in results and images that trained professionals miss. It has the mind power to ask if every single pixel in the photo is healthy or if every molecule in the blood test is at the right level even if things don’t appear instantly to the doctor. It can do it before the doctor opens the envelope, which doesn’t get rid of the doctor, just the envelope. The work in creative AI systems at this time is in the inventive field that can be termed Inferpolation. This is a stage beyond extrapolation because the result is completely new and independent from the constraints applied by the original data. Using a door handle to open a beer is perhaps a simple example of this in action, where we use a thing that is completely out of context to achieve a goal that it was never designed to achieve. Putting the device on another device, like the iPhone, is another example. You can’t get a computer that knows everything about mp3 players to suddenly know about phones, what would it take to program an mp3 player to philosophise on other purposes it could have? You’d have to give it a lot of internal knowledge and an ability to draw upon it to create hypothetical situations. The system needs to link multidisciplinary sources in hypothetical scenarios to test unknown theories without instruction. Humans do this all the time, but can a computer? Could a piece of software intuitively open a metaphorical beer with a symbolic door handle? Knowing how we do it, and why, is the possibly best way to learning how to program the machine to imitate it. Humans are not like machines in which we can actively process lots of information at the same time. We rely on our intuition to learn what our subconscious is telling us. Th subconscious is a lot more like the machine. It doesn’t rely on big picture models and imagined gap filling; it simply has experience built in over millions of generations of evolution. The conscious mind must infer all kinds of things, there is no way the brain can absorb every detail our eyes, ears, skin, and so on are telling us. It takes short cuts based on what we’ve learned. The imagination fills in the gaps so when we see a smoking chimney, we already see the roof, and the building, the details are built up as we look more, yet the basic construction can be inferred from the size of the plume, the location of the building, and the material the chimney is made from. Every new information nugget can be used like a seed to grow the bigger picture before we’ve had a chance to study it. This is why we fail to notice many things if they’re out of context and we’re giving our attention to one particular focus. A large database of interconnected ideas and knowledge is required for this to work. It takes a vast reservoir of known examples that we use our subconscious to process. A machine will have a database of information that is interlinked to itself with associative data, and it uses it at the speed of electricity. How does this database work and how is it acquired? The resource of information that a machine must use for its decision making is defined in two distinct ways. Expert systems are given a set amount of data to use that is designed by a human being. These machines do exactly what they are told or what their set rules allow them to do according to the rigid parameters in the program. The best-known example if this in action is the AI opponent in a video game. The difficulty can be set which enables the character to do more or fewer moves in its efforts to defeat you. It then is given a list of available moves and instructions on how to execute them. You, the player, outsmart the computer or you don’t. In the old days, they never learned from your tactics although they knew how to adjust over time to throw you off. Throw in a random variable or two to make it more like real life, and you get a good game each time. It’s not that intelligent, it’s just doing what it’s told extremely well. The techniques of programming machines to beat human opponents were perfected with chess computers. A set list of available moves is given, and the machine tests each one in turn to decide the most effective move. It can be taught how to forward plan by several moves and anticipate the human interaction for various outcomes so it can assess the best likelihood of a win. This was achieved in the 20th Century and was the result of years of programming work across several projects. When the outcomes are so various that it’s impossible to account for them all, a creative and intuitive element is required. The real world is not like chess, we have infinite squares and moves each, and there are billions of us. How do we ask an AI to think about and generate responses that account for this? The answer is in the other model of artificial intelligence. The learning model is not the expert system. In fact, if you ask a learning model to play a game of something as simple as connect 4, it probably won’t win for at least 50 games. This is because it is deliberately given zero initial information. Instead, the system is given the task of learning for itself to fulfil a goal. It is then given a positive reinforcement for a correct response and a negative reinforcement for an incorrect one. It’s treated much more like a child or a pet, who given the right guidance, can grow up to be a fully functioning and responsible member of the household. The learning system is given the information sources that it then uses in hypothetical and scientific examination ways that are programmed into its learning model. These elements are under human control, however the end results and the ways it chooses to apply the information are not. Provided we do not give it goals that are counter intuitive to humanity, it won’t look for them. What is stopping it from determining harmful actions on its own, to fulfil a different goal, like an end to poverty? Killing everyone surely would end poverty in a computer’s eyes unless it already knew that was never to be done. This means that this powerful tool must have ingrained contingencies that it can’t work around regardless of its goal and the line of best fit it has determined. How do we know what these are? Perhaps teaching it the laws that human beings must live by would be a good start, and a procedure that results in shut down if one is about to be broken. Now, where have I seen that before? It's probably a good idea to grab yourself some professional tuition on AI engineering and use from skilled computer scientists. Check them out.  Gothic botanicals, moody petals, stunning depth and ethereal majesty. The mysterious and enchanting allure of the gothic design has swept up aesthetic all the way from Victorian England to the modern and global post-punk sound spheres. Bram Stoker would rise from his grave to witness the beautiful and mind-capturing gothic scene that has grown from the initial idea of night creatures and lust for the dark. One way to harmonise our surroundings with the mental landscape we enjoy is to grow plants that mirror our ideal. For gothic and dark loving people, a fascinating array of plants and flowers are available to add a sense of nature and a dapple of shade to any sunny spot. The natural world is full of inspiration and creative motivation. The slow, gradual, and stalwart ability of plants to push on through and grow tall over time, given the right ingredients, is a lesson for us all. Don’t rush, build little by little, and in time you’ll be a stunning example of your kind. Taking in the appreciation for subtle growth and gradual change that results in a beautiful outcome is something even the gloomiest minded of people can take home. You can try growing any number of these following black and dark foliage plants for your gothic garden. Be it a windowsill, little back yard, or an acre of free-range moor with mist and moonlight, you can create a magical and mysterious gothic landscape all for yourself where you can sip red wine and listen to Bauhaus in comfort. The Ultimate List of Black Flowers & Plants for Your Gothic Garden Mesmerizing Black Blooms
View on Amazon  Black Hollyhock  Tulip Queen of the Night
 Calla Lily 'Black Forest'
View on Amazon  Nemophila 'Penny Black'
View on Amazon  Persian Lily (Fritillaria persica)  Black Bearded Iris Dark Foliage & Gothic Greens
View on Amazon  Black Mondo Grass (Ophiopogon planiscapus 'Nigrescens')
View on Amazon  Elderberry 'Black Beauty' 
View on Amazon  Columbine 'Black Barlow'  Ninebark 'Diabolo'
View on Amazon  False Shamrock (Oxalis triangularis 'Black') Unique & Mysterious
View on Amazon  Black Bat Flower (Tacca chantrieri)  Black Velvet Petunia
View on Amazon  Pepper 'Black Pearl'
View on Amazon  Sunflower 'Moulin Rouge'  ZZ Plant 'Raven' Remember, when you grow plants and flowers, they require the right amounts of sunlight, water, and food. It’s easy when you know how so make sure to read up on the right methods for the species you decide to try. Want to go the extra mile and become one with mother nature? Try these affordable and professional botany courses with experienced tutors. 
Every time I visit The Internet Archive, I’m overwhelmed by the sheer number of options. I could spend hours searching the database for something worth my time, something that fits the mood of the moment. One day I might want classic Windows and Dos games, and another I might want to watch some weird Soviet cartoon I don’t understand. Something we can all appreciate is classic cinema. The way they used to make films was a lot more akin to a theatre production with studios and stages with hand-made special effects. The older the film, the more rudimentary the technology and technique. When we trace back storylines and character development, we can see themes and similarities that still prevail today. When we want to examine the depth of the human imagination and film industry inventiveness, turning to fantasy and sci-fi is probably going to yield a good harvest. The boat is pushed with each fantastical idea, the methods of getting the shot, the costumes and the effects, we can enjoy the production for what it is for its own place in time. So, we love to complain about the modern film with its CGI and AI generated what nots. So why not submerge your cultural imagination in something from a time when computers were counting machines. To save you time and effort, I’ve created this list of some top watch-worthy films from the Science Fiction and Fantasy genre that are completely free and downloadable on The Internet Archive. You can watch the online from the website or select the video file for download and take it with you. There are plenty of others on the site for you to browse if you have time. These selected ones are the titles that have stood out as unusual and entertaining. Fantastic Planet by Rene Laloux 1973 The Revenge of a Kinematograph Cameraman (silent) by Wladyslaw Starewicz 1912 Lady Frankenstein by Umberto Borsato 1970 Satan’s Cheerleaders by Greydon Clark 1977 Inner Sanctum by Lew Landers 1948 House On Haunted Hill by William Castle 1959 Day The Earth Stood Still starring Micheal Rennie (colourised) 1951 Spellbound by Alfred Hitchcock 1945 Gulliver’s Travels (animation) by Fleischer Studios 1939 Kagemusha by Akira Kurosawa 1980 Earth Vs The Flying Saucers by Sam Katzman (colourised) 1956 Cosmos War Of The Planets by Louis Alex 1977 The Lost World by Jamie White 1925 Creature From The Black Lagoon starring Richard Carlson (colourised) 1954 Tarantula starring John Agar (colourised) 1955 Horror Express with Christopher Lee and Peter Cushing 1973 Bloody Pit Of Horror by Francesco Merli and Ralph Zucker 1965 Killers From Space by W. D. Wilder 1954 Daughters Of Darkness by Harry Kumel 1971 Grave Of The Vampire by John Hayes 1974 Nosferatu 1922 Waxworks by Conrad Veidt 1929 Invasion Of The Body Snatchers by Walter Wanger (colourised) 1956 The Deadly Mantis starring Craig Stevens (colourised) 1957 It Came From Outer Space Starring Richard Carlson and Barbara Rush (colourised) 1953 Kronos by Jeff Morrow (colourised) 1957 Destroy All Planets by Masaichi Nagata 1968 The Golem starring Paul Wegener 1920 The Crawling Eye starring Forrest Tucker (colourised) 1958 Silent Night, Bloody Night by Theodore Gershuny 1972 Alice In Wonderland by W.W. Young (silent) 1915 The Monster That Challenged The World starring Tim Holt (colourised) 1957 First Spaceship On Venus by Hans Mahlich 1960 Captain Kronos Vampire Hunter by Brian Clemens 1974 In The Year 2889 by Larry Buchanan 1967 When Worlds Collide by Rudolph Mate and George Pal 1951 The Yesterday Machine 1963 Haxan (silent) 1922 Attack From Space Koreyoshi Akasaka 1969 Nightmare Castle by Carlo Caiano 1965 Beat The Devil starring Humphrey Bogart 1953 Revenge Of The Creature From The Black Lagoon by Jack Arnold 1955 Driller Killer uncut by Abel Ferrara 1979 The Terror by Roger Corman 1963 City Of The Dead / Horror Hotel by Ben Arbeid 1960 Curse Of The Demon starring Dana Andrews (colourised) 1957 White Zombie by Edward Halperin 1932 Utopia by Raymond Egar 1951 I Eat Your Skin by Del Tenney 1971 Attack Of The Monsters by Masaichi Nagata 1968 The Monolith Monsters 1957 Evil Brain From Outer Space starring Ken Utsui 1964 The Creature Walks Among Us by John Sherwood 1956 So, there are plenty of titles here for you to enjoy, and it’s just a select pick from the massive list on the archive. I’ve done my best to ignore things that are well-known or not on theme. Here are some fun and creepy, sometimes fascinating, films to download, play, put on over parties with the volume down, or whatever you want. Have fun. PS. The Internet Archive is a crowd funded resource much like Alterative Fruit. Once you’ve tipped this journal, make sure to give them a little something too. If making films and the art of film making is a subject you’re interested in, there’s nothing quite like learning from professional tutors, with experience, reviews, and the human touch. Browse today. |
CategoriesAuthorAlternative Fruit by Rowan B. Colver 
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July 2025
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