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Karnov for arcade (Data East/1987). A game about a circus strongman who can use special items for different functions (ladders, bombs, etc.). Goal is to collect the pieces of a lost treasure map. Did cameos in other Data East titles, like Bad Dudes and Fighter's History, becoming a kind...

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Dante retro dev 💾

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11,866 просмотров • 6 дней назад •via X (Twitter)

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COMBAT SCHOOL (Konami 1987) Also known as BOOT CAMP, it plays like earlier Decathlon or Hyper Sports games but it's about doing basic training for the USMC. Great and varied, it was ported to C64, Amstrad CPC, ZX Spectrum and MS-DOS PC. #コンバットスクール #arcade #2D #pixelart
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COMBAT SCHOOL (Konami 1987) Also known as BOOT CAMP, it plays like earlier Decathlon or Hyper Sports games but it's about doing basic training for the USMC. Great and varied, it was ported to C64, Amstrad CPC, ZX Spectrum and MS-DOS PC. #コンバットスクール #arcade #2D #pixelart

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Express Raider (known as Western Express in Japan) - Data East/1986. Classic Wild West arcade game where you play as a train robber, punching and shooting your way across moving locomotives to steal gold. A popular arcade title, it received conversions to the Amstrad CPC, Commodore 64, ZX Spectrum, and modern platforms such as the Nintendo Switch and PC (GOG and Steam).
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Express Raider (known as Western Express in Japan) - Data East/1986. Classic Wild West arcade game where you play as a train robber, punching and shooting your way across moving locomotives to steal gold. A popular arcade title, it received conversions to the Amstrad CPC, Commodore 64, ZX Spectrum, and modern platforms such as the Nintendo Switch and PC (GOG and Steam).

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Atomic Runner for the the Sega Mega Drive/Genesis (Data East/1992). Highly challenging action-platformer ported from Data East's 1988 arcade game, Chelnov. Considered superior to the original and a cult classic, standing out for its unique forced-scrolling gameplay, upgraded pixel art and memorable music. Also released on the X68000 and Wii Virtual Console (Japan).
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Atomic Runner for the the Sega Mega Drive/Genesis (Data East/1992). Highly challenging action-platformer ported from Data East's 1988 arcade game, Chelnov. Considered superior to the original and a cult classic, standing out for its unique forced-scrolling gameplay, upgraded pixel art and memorable music. Also released on the X68000 and Wii Virtual Console (Japan).

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IMPOSSIBLE MISSION for C64 (Dennis Caswell/Epyx/1984) Absolute classic. Randomized layouts inspired by Rogue, early use of digitized speech, smooth somersault animation (Dennis used a book about athletics as drawing reference) and that checkerboard puzzle which is like the Simon toy (lower to higher pitch) giving a password. On top of all that, the actual platform gameplay is really solid. Also available for Apple II, Atari 7800, ZX Spectrum, Amstrad CPC, Acorn Electron, BBC Micro, and Master System. Revamped versions were released for PSP, DS, Wii and Switch. #C64Reposts #Commodore
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IMPOSSIBLE MISSION for C64 (Dennis Caswell/Epyx/1984) Absolute classic. Randomized layouts inspired by Rogue, early use of digitized speech, smooth somersault animation (Dennis used a book about athletics as drawing reference) and that checkerboard puzzle which is like the Simon toy (lower to higher pitch) giving a password. On top of all that, the actual platform gameplay is really solid. Also available for Apple II, Atari 7800, ZX Spectrum, Amstrad CPC, Acorn Electron, BBC Micro, and Master System. Revamped versions were released for PSP, DS, Wii and Switch. #C64Reposts #Commodore

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Some arcade games by Data East Corporation (DECO). It was a prolific Japanese video game, electronics, and pinball company known for developing numerous arcade and home console titles. Founded 50 years ago (April 20, 1976) by Tetsuo Fukuda in Tokyo, declared bankruptcy in 2003, subsequently selling many IP rights to G-Mode.
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Some arcade games by Data East Corporation (DECO). It was a prolific Japanese video game, electronics, and pinball company known for developing numerous arcade and home console titles. Founded 50 years ago (April 20, 1976) by Tetsuo Fukuda in Tokyo, declared bankruptcy in 2003, subsequently selling many IP rights to G-Mode.

Dante retro dev 💾

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Iran’s Foreign Ministry spokesperson says the US does not care about the security of its allies in the Middle East, and that negotiations are like a game of snakes and ladders due to "contradictory" demands. Asked about the risk of a return to full-scale war, he said Iran must be prepared for “every scenario.”
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Iran’s Foreign Ministry spokesperson says the US does not care about the security of its allies in the Middle East, and that negotiations are like a game of snakes and ladders due to "contradictory" demands. Asked about the risk of a return to full-scale war, he said Iran must be prepared for “every scenario.”

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Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!
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"Data Center Alley" a section of Virginia with the densest concentration of data centers in the country, caused the power to flicker across the East Coast. On Wednesday, July 22nd the electricity flickered on and off for about 10 minutes throughout the Eastern U.S., from Chicago to Boston to Miami. The cause appears to be a concentration of data centers straining the grid. Video from: NBC4 Washington
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"Data Center Alley" a section of Virginia with the densest concentration of data centers in the country, caused the power to flicker across the East Coast. On Wednesday, July 22nd the electricity flickered on and off for about 10 minutes throughout the Eastern U.S., from Chicago to Boston to Miami. The cause appears to be a concentration of data centers straining the grid. Video from: NBC4 Washington

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Get your ticket today. Buy your ticket for the Data Science East Africa Conference 2026. This is a great opportunity to learn, network, and build with other like minded peers in the space. Visit and secure your ticket now.
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Get your ticket today. Buy your ticket for the Data Science East Africa Conference 2026. This is a great opportunity to learn, network, and build with other like minded peers in the space. Visit and secure your ticket now.

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Instagram launches forced Data Collection to use their app If you login and get this prompt, you must accept data all this data collection or you will be promoted to log out and not allowed to use the App Here is a full down of what’s mandatory to give up to use Instagram: Collection and use of personal data: They collect our activity on Instagram (posts, stories, likes, comments, searches, time spent), device info, IP address, contacts (if synced), messages, location (when enabled), demographics, and inferred interests Sharing of data with other Meta companies. They take all the personal data they collected and share across Facebook, WhatsApp, Threads, Oculus, etc. Cross-border transfers of personal data: Your data is sent and stored in the US and other countries where Meta has offices/data centers or partners. Location information: Precise location (GPS when you use features like Stories or check-ins), approximate location from IP/Wi-Fi, and location-based activity history. Stop using META products
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Instagram launches forced Data Collection to use their app If you login and get this prompt, you must accept data all this data collection or you will be promoted to log out and not allowed to use the App Here is a full down of what’s mandatory to give up to use Instagram: Collection and use of personal data: They collect our activity on Instagram (posts, stories, likes, comments, searches, time spent), device info, IP address, contacts (if synced), messages, location (when enabled), demographics, and inferred interests Sharing of data with other Meta companies. They take all the personal data they collected and share across Facebook, WhatsApp, Threads, Oculus, etc. Cross-border transfers of personal data: Your data is sent and stored in the US and other countries where Meta has offices/data centers or partners. Location information: Precise location (GPS when you use features like Stories or check-ins), approximate location from IP/Wi-Fi, and location-based activity history. Stop using META products

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New PNAS paper. Historical GDP per capita data is scarce, but data on the places of birth, death, and occupations of famous individuals is abundant. In this paper we estimate the historical GDP per capita of hundreds of regions in Europe and North America using a machine learning model that leveraged data on about 500k famous biographies. Our estimates more-or-less quadruple the availability of historical GDP per capita estimates for the last 700 years. So why use biographies to augment historical GDP per capita data? Biographical data contains information about people who might have contributed directly to economic growth, like James Watt, or that were attracted to wealthy places looking for patrons, like Michelangelo. So we--mainly Philipp (Philipp Koch)--used this data to construct hundreds of features describing each European region. Then, we trained a machine learning model to find the features that explained most of the variance in a cross-validation test, where we split regions multiple times into a training set and a test set. On average, the model explained about 90% of the variance in GDP per capita of the regions it had not seen during training. But we wanted to go further, and Philipp really went to town by looking at different ways to validate our estimates. We found our estimates correlate positively with historical measures of wellbeing, church building activity, urbanization, and body height. We also used these measures to reproduce the basic Atlantic trade result of Acemoglu, Johnson, and Robison and to explore the economic consequences of the famous Lisbon earthquake of 1755. But what I personally loved most about this project, other than working with Philipp Koch and V, is that it shows that we can use machine learning methods not only to explore the future, but the past. There is a bright and growing future in the use of machine learning for economic history. Hope you enjoy the paper and the data. You can find links to the paper and a data exploration tool in the first comment.
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New PNAS paper. Historical GDP per capita data is scarce, but data on the places of birth, death, and occupations of famous individuals is abundant. In this paper we estimate the historical GDP per capita of hundreds of regions in Europe and North America using a machine learning model that leveraged data on about 500k famous biographies. Our estimates more-or-less quadruple the availability of historical GDP per capita estimates for the last 700 years. So why use biographies to augment historical GDP per capita data? Biographical data contains information about people who might have contributed directly to economic growth, like James Watt, or that were attracted to wealthy places looking for patrons, like Michelangelo. So we--mainly Philipp (Philipp Koch)--used this data to construct hundreds of features describing each European region. Then, we trained a machine learning model to find the features that explained most of the variance in a cross-validation test, where we split regions multiple times into a training set and a test set. On average, the model explained about 90% of the variance in GDP per capita of the regions it had not seen during training. But we wanted to go further, and Philipp really went to town by looking at different ways to validate our estimates. We found our estimates correlate positively with historical measures of wellbeing, church building activity, urbanization, and body height. We also used these measures to reproduce the basic Atlantic trade result of Acemoglu, Johnson, and Robison and to explore the economic consequences of the famous Lisbon earthquake of 1755. But what I personally loved most about this project, other than working with Philipp Koch and V, is that it shows that we can use machine learning methods not only to explore the future, but the past. There is a bright and growing future in the use of machine learning for economic history. Hope you enjoy the paper and the data. You can find links to the paper and a data exploration tool in the first comment.

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No longer a ‘conspiracy theory’ Online retailers are accessing your data and then adjusting prices for items based on that data Airlines are being caught adjusting prices based on data too “This holiday season, you and your neighbor could be shopping for the exact same item and pay different prices — surveillance pricing is and how your personal data plays a role. You may be shopping for gifts from the comfort of your couch, but stores can still see who you are. Most of these companies are charging you a different price based on some data they have about you. It could be your location, it could be your proximity to the store, it could be your shopping history, knowing that you bought a product previously and are willing pay for it again.” “Consumer watchdog president Jamie Court says surveillance pricing is nearly impossible to avoid — Court says his organization has evidence all the major retailers use personal algorithms to nudge a price up or down, targeting data from your Amazon cart, Uber rides, or even the brand of laptop you're using to shop” “For those traveling for the holidays. Airlines will charge you a different price depending upon how many times you go to the website. “Currently, there is no federal regulation for companies that use surveillance pricing. We reached out to the FTC”
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No longer a ‘conspiracy theory’ Online retailers are accessing your data and then adjusting prices for items based on that data Airlines are being caught adjusting prices based on data too “This holiday season, you and your neighbor could be shopping for the exact same item and pay different prices — surveillance pricing is and how your personal data plays a role. You may be shopping for gifts from the comfort of your couch, but stores can still see who you are. Most of these companies are charging you a different price based on some data they have about you. It could be your location, it could be your proximity to the store, it could be your shopping history, knowing that you bought a product previously and are willing pay for it again.” “Consumer watchdog president Jamie Court says surveillance pricing is nearly impossible to avoid — Court says his organization has evidence all the major retailers use personal algorithms to nudge a price up or down, targeting data from your Amazon cart, Uber rides, or even the brand of laptop you're using to shop” “For those traveling for the holidays. Airlines will charge you a different price depending upon how many times you go to the website. “Currently, there is no federal regulation for companies that use surveillance pricing. We reached out to the FTC”

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Who played this epic masterpiece of gaming history? Some games feel truly timeless. Stunt Car Racer (MicroStyle, 1989) is one of them. It was designed by Geoff Crammond, the genius behind other legendary titles such as The Sentinel and Formula One Grand Prix. The iconic “vroooooooooooom” when you rev it up, the cleverly drawn crack along the upper frame of the car to show damage, the incredible physics, and those massive jumps across insane ramps… What more is there to say? It was a near-perfect game in its time and remains a whole lot of fun 37 years later. Hopefully, it will still be talked about by future generations who haven’t even been born yet. Stunt Car Racer was available on the “big 6” platforms back in the day: Commodore 64, Amiga, Amstrad CPC, Atari ST, DOS, and ZX Spectrum.
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Who played this epic masterpiece of gaming history? Some games feel truly timeless. Stunt Car Racer (MicroStyle, 1989) is one of them. It was designed by Geoff Crammond, the genius behind other legendary titles such as The Sentinel and Formula One Grand Prix. The iconic “vroooooooooooom” when you rev it up, the cleverly drawn crack along the upper frame of the car to show damage, the incredible physics, and those massive jumps across insane ramps… What more is there to say? It was a near-perfect game in its time and remains a whole lot of fun 37 years later. Hopefully, it will still be talked about by future generations who haven’t even been born yet. Stunt Car Racer was available on the “big 6” platforms back in the day: Commodore 64, Amiga, Amstrad CPC, Atari ST, DOS, and ZX Spectrum.

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Shock Trooper (Saurus/SNK/1997) is a highly regarded top-down run-and-gun arcade game for the Neo Geo MVS arcade system. The game has been ported to several platforms as part of the ACA NEOGEO series, PC (Steam & GOG) and other collections such as SNK Arcade Classics Vol. 1 (PS2/PSP/Wii).
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Shock Trooper (Saurus/SNK/1997) is a highly regarded top-down run-and-gun arcade game for the Neo Geo MVS arcade system. The game has been ported to several platforms as part of the ACA NEOGEO series, PC (Steam & GOG) and other collections such as SNK Arcade Classics Vol. 1 (PS2/PSP/Wii).

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"If you're an analytical SaaS company, it's over. It's over." - Palo Alto Networks CEO Nikesh Arora "What is an analytical SaaS company? It is a company that says, “I'm going to collect a lot of data for you and analyze it for you.” I don't need you to analyze it for me. I can run models against the data and analyze it myself. Think about it: almost every SaaS company has a marketplace. You can buy applications from the Salesforce Marketplace. What do those applications say? “You have Salesforce data. I'm a marketplace app. Use me, and I'll help you analyze that data.” But I don't need to do that. You don't need those applications anymore. I can simply run an LLM against the data. Therefore, all the additional functionality that has traditionally been sold to us as incremental software modules may no longer need to be sold separately. I would much rather have an LLM run against the data." ---- From "All-In Podcast" YouTube channel, (full video link in comment)
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"If you're an analytical SaaS company, it's over. It's over." - Palo Alto Networks CEO Nikesh Arora "What is an analytical SaaS company? It is a company that says, “I'm going to collect a lot of data for you and analyze it for you.” I don't need you to analyze it for me. I can run models against the data and analyze it myself. Think about it: almost every SaaS company has a marketplace. You can buy applications from the Salesforce Marketplace. What do those applications say? “You have Salesforce data. I'm a marketplace app. Use me, and I'll help you analyze that data.” But I don't need to do that. You don't need those applications anymore. I can simply run an LLM against the data. Therefore, all the additional functionality that has traditionally been sold to us as incremental software modules may no longer need to be sold separately. I would much rather have an LLM run against the data." ---- From "All-In Podcast" YouTube channel, (full video link in comment)

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🚨 JUST IN: Florida Gov. Ron DeSantis has just BANNED AI data centers from using up all the water needed by citizens during a drought And the law BANS utility companies from charging higher prices because of data centers "How are you going to say that somehow the water can go to a data center when we need to water for our own people and for the core functions of our society?"

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Sam Altman Hi Sam Altman I built a gameboy emulator for NYC that streams real-time city data (subways, weather, ferries, etc) all layered on a 3d map of NYC! All data exists in a spatial intelligence layer that agents can use to experience your fav places in the city! Should I do SF next?
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Sam Altman Hi Sam Altman I built a gameboy emulator for NYC that streams real-time city data (subways, weather, ferries, etc) all layered on a 3d map of NYC! All data exists in a spatial intelligence layer that agents can use to experience your fav places in the city! Should I do SF next?

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