Archive for Artificial ntelligence

Artificial Intelligence Firms You Should Know

Artificial Intelligence Firms You should KnowOn June 20th, 2024, artificial intelligence darling Nvidia surpassed $3 trillion in market cap. As a result, the chip maker became the most valuable company in the world, beating out Microsoft and Apple. Some are wondering if Nvidia’s current valuation is justified and sustainable. Some are arguing that we’re still just at the beginning of the Generative AI boom. However, others aren’t yet convinced that AI will deliver on the hype that tools like ChatGPT have created.

Generative artificial intelligence

In this context, Generative artificial intelligence (GenAI) refers to a trending class of machine learning applications that are able to create new data, including text, images, video, or sounds, based on a large dataset on which it has been trained. Here are some other GenAI firms that could be some alternate firms to check out if NVIDIA is too rich to buy at this level.

Artificial Intelligence vendors

Adobe

Adobe is most famous for its creative software like PhotoShop. However, the company has expanded into artificial intelligence. Adobe planned to acquire Figma in a $20 billion deal announced in September 2022. They called off the deal in December 2023 due to antitrust concerns in Europe. Adobe’s latest image generation model, Firefly 3, announced in April 2024. The model brings a new level of high-quality images and better understanding of prompts given.

  • Key Products: Adobe Sensei, Adobe Firefly, AI Assistant
  • Company value: $200.86 billion

Alphabet (Google)

Google logoGoogle and its parent company Alphabet expanded into artificial intelligence with the formation of its Google AI division in 2017. In 2023, the company announced BARD. The company designed BARD to compete with Microsoft’s integration of ChatGPT into its Bing search engine. The early release was marked by reported internal disapproval of the product. 

  • Key Products: Gemini, Vertex AI, Gemini for Google Workspace
  • Company value: $1.72 trillion

Amazon Web Services (AWS)

Amazon Web ServicesKnown for its scalable cloud infrastructure, Amazon has also thrown its virtual hat into artificial intelligence ring. Yet, the e-commerce and cloud giant finds itself playing catch-up in generative AI.

According to Business Insider’s sources, a stealth internal project code-named Metis, is it next step in AI.  “Metis” will be powered by an internal Amazon AI model called Olympus. The latter will power Remarkable Alexa, a new, more capable version of Alexa for a  monthly subscription fee

Metis will reportedly use a technique called retrieval-augmented generation (RAG), according to BI. RAG will enable Metis to retrieve information from beyond the original data used to train the underlying model. This means Metis will offer more up-to-date responses like the latest stock prices or medical reaserach, while other chatbots still produce inaccurate or outdated information.

AWS offers a suite of AI services, including GenAI models for text, speech and image processing.

  • Key Products: Amazon Bedrock, Amazon Q, Amazon CodeWhisperer, Amazon SageMaker
  • Company value: $1.79 trillion

Anthropic logoAnthropic

Anthropic announced the third generation of its Claude generative AI chatbot, which competes with OpenAI’s ChatGPT and Google’s Bard. Claude AI is a constitutional chatbot. It has been trained to make judgments based on a set of principles taken from documents including the 1948 UN Declaration and Apple’s terms of service, which expands to issues in the digital domain. Claude 2 has complex choice-making capabilities and scored 76.5% on the multiple choice section of the bar exam. While it hasn’t quite had the publicity of the big artificial intelligence chatbots it looks like Anthropic might have created a worthy competitor.

  • Key Products: Claude 3, Claude API
  • Company value: $15 billion

Cohere

Cohere logoCohere is a company which focuses on building artificial intelligence models for enterprise customers. Enterprise customers can use their own data to train their AI models, without sharing that data. Their primary focus is on creating AI systems that can: understand, generate and, interact with human language.

  • Key Products: Command, Embed, Chat, Generate, Semantic Search
  • Company value: $2.2 billion

IBM

IBM logoIBM’s Watson was the first artificial intelligence language model technology to attain global notoriety, as a result of its 2011 victory on the quiz show Jeopardy!. Watson was question-answering platform, initially developed from 2004-2011. Since then, its deep learning capabilities have been applied to a wide range of industries, including healthcare, cuisine, hospitality, water conservation, and more. IBM has continued to evolve it’s AI capabilities. In the past 5 years, IBM has filed 1,591 AI-related US patent applications. In April 2024, IBM announced its acquisition of HasiCorp. for $6.4 billion.

  • Key Products: WatsonX.ai, Code Assistant, Slate, Granite
  • Company value: $153.76 billion

Jasper

Jasper AIJasper uses artificial intelligence to help businesses write marketing content. They claim it can write the same content much faster than a human being can, in a tone of voice that customers relate to and find familiar. It helps businesses generate consistent and effective digital marketing content, from blog posts to social media updates.

  • Key Products: Jasper, Jasper API, Jasper AI Copilot
  • Company value: $1.2 billion

Meta (Facebook)

Meta logoMeta (formerly known as Facebook) has grown to where 3.14 billion people interact with one of their platform’s daily. The company is known for its social media platforms, including Facebook, Instagram, WhatsApp, and Oculus. While the company has faced criticisms harmful misinformation, polarizing political content, and data leaks.

For years, Meta has used artificial intelligence to recommend posts in our feeds, moderate content, and target ads behind the scenes in Instagram and Facebook.

  • Key Products: Meta AI, Llama 2.0, Llama 3.0 (coming soon), Seamless Communication models
  • Company value: $1.252 trillion

Microsoft largest artificial intelligence company

Microsoft logoMicrosoft has claimed to be the world’s largest artificial intelligence company. MSFT has made a $10 billion investment in OpenAI in January 2023. They then integrated ChatGPT generative AI chatbot and Dall-E image generation into the Bing search engine and Edge web browser.

  • Key Products: Microsoft Copilot, Copilot for Microsoft 365, Microsoft Copilot Studio, Microsoft Copilot in Bing
  • Company value: $3.01 trillion

Midjourney

Midjourney.comMidjourney AI specializes in creating AI-powered tools that generate realistic and imaginative images from text descriptions. It offers tiered subscriptions and allows users to monetize their AI-assisted artwork. It’s integrated into various platforms, including Discord and Microsoft Edge.

In late March 2023, Midjourney suspended free trials due to people abusing the system.

  • Key Products: Midjourney AI
  • Company value: $10 billion

NVIDIA king of artificial intelligence

NVIDIA logoNVIDIA started working on 3D graphics graphics processing units (GPUs) for multimedia and gaming companies in 1993. The company also began creating artificial intelligence applications back in 2012. Today, NVIDIA is generally considered the leader in AI technology as it is at the forefront of AI and is developing software, chips and AI-related services.The company commands 87% of the GPU market and has had a hand in major AI technology advancements, including ChatGPT, which was trained using 10,000 NVIDIA GPUs. The NVIDIA NeMO LLM’s status as one of the most advanced large language models, along with a new partnership with Microsoft, further cement its place among prominent AI companies.

  • Key Products: NVIDIA AI, NVIDIA NeMo, NVIDIA BioNeMo, NVIDIA Picasso, various chips and GPUs
  • Company value: $2.14 trillion

OpenAI sparked the artificial intelligence boom

OpenAI logoOpenAI continues to lead the GenAI space with its GPT-4 model, widely used across industries for natural language processing tasks. OpenAI’s tools are integrated into numerous applications, from customer service chatbots to creative writing assistants.

In contrast, OpenAI has famously scooped up data from everywhere to train its chatbots, like Reddit. And, when a user uploads information into OpenAI to ask ChatGPT to do a task, OpenAI uses that data to train its models for everyone’s use. Users can opt out of that, but it’s one of the reasons why companies warn their employees not to share data with OpenAI.

  • Key Products: GPT-4, ChatGPT, DALL-E 3, Sora
  • Company value: $80 billion

Stability AI

Stability.ai logoStability AI excels in creating advanced AI models, particularly the Stable Diffusion series, that generate high-quality, realistic images from text prompts. They offer models in multiple languages and for commercial use, emphasizing photorealism and complex prompt processing.

  • Key Products: Stable Diffusion XL, Stable Video Diffusion, Stable Audio, Stable Zero123

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Ralph Bach has been in IT for a while and has blogged from his Bach Seat about IT, careers and anything else that catches his attention since 2005. You can follow me on Facebook. Email the Bach Seat here.

HPE Buying into Artificial Intelligence Market

HPE Buying into Artificial Intelligence MarketIn the first mega-deal of 2024, Hewlett Packard Enterprise (HPE), the offshoot of industry pioneer Hewlett-Packard, announced a $14 billion acquisition deal with networking equipment maker Juniper Networks (JNPR). HPE is positioning the deal as an artificial intelligence play. HPE CEO Antonio Neri claimed the acquisition was, “… a major leap forward in our AI and hybrid cloud strategy.

HPE logoHPE is buying Juniper for $40 per share. That is a 32% premium above Juniper’s closing stock price on the day before the HPE announcement. The deal is expected to close in early 2025. Juniper CEO Rami Rahim will lead the combined HPE networking business and report to HPE’s Neri. The deal will add $11.2 billion to HPE debt, including $1.7 billion of assumed Juniper debt. HPE will pay for the acquisition in part through cash from a 2023 sale of its remaining interest in China-based joint venture H3C for $3.5 billion.

About Juniper

Juniper logoJuniper has been under performing of late. The company’s stock price fell about 8% in 2023, while the NASDAQ Composite gained 43%. The firm has struggled against Cisco (CSCO) in the networking equipment market. Juniper Networks was founded in 1996. It has grown its networking product line-up, including routers, switches, and security products. But the company also runs Mist AI. Mist AI is an AI and machine learning business that specializes in AI-powered network management.

About HPE

HPE has a long history of acquisitions.

  • In 2001 the original HP purchased Compaq for $25 billion.
  • HPE has a long history of acquisitions.HP acquired services provider Electronic Data Systems for $13.9 billion in 2008.
  • In November 2009 HP acquired switch maker 3Com for $2.7 billion. 
  • 2010 saw HP spend $2.35 billion on the acquisition of 3PAR.
  • In 2015, HP spun out its software, services, PCs, and printers to a new firm called HP Inc.. HPE kept the server, storage, networking, tech support, consulting, and financing for data center gear businesses.
  • HP acquired Aruba Networks in 2015 for $2.7 billion.
  • During 2017 HPE bought flash storage maker Nimble Storage for $1 billion.
  • HPE bought Cray Supercomputers in 2019.

Artificial Intelligence

HPE has already benefited from AI industry growth. It told investors in November that orders for servers containing accelerated processing units for use in Artificial Intelligence Market had added up to 32% of its server segment. Overall net revenue for 2023 was $7.4 billion.

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This latest HPE acquisition follows a familiar pattern to HPE’s other networking acquisitions over the last several decades. They seem to be trying to buy market share. And the results have been meh.

When I started in the business it was Compaq Deskpro’s on the desktop and Proliant’s were the go-to servers. We had an end-to-end 3Com network. Today we don’t buy HP desktops and the network guys don’t even know what a 3Com is. Both HPE and Juniper have struggled behind Cisco. It is unlikely the merger will change that.

HPE seems to be hanging its hat on growth in the server sector to support AI deployments. I am sure they want to bundle the Mist Artificial Intelligence on a server and a 3PAR SAN and sell it to us as a network management/security solution, at some inflated price. Who remembers HP OpenView?

Good luck HPE.

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Ralph Bach has been in IT long enough to know better and has blogged from his Bach Seat about IT, careers, and anything else that catches his attention since 2005. You can follow him on LinkedInFacebook, and Twitter. Email the Bach Seat here.

Does This Dog Exist

Jessie and Wiley resuce dogsDog rescue Wags & Walks wants to know if you can spot the real puppy in a pack of artificial intelligence (AI) generated dogs. The rescue with locations in Nashville and Los Angeles features the game This Dog Exists. This Dog Exists is designed to promote the adoption of homeless pooches.  The game is a clever use of artificial intelligence that serves the greater good. 

Wags & Walks
This Dog Exists was created by Matt Reed, the creative technologist at the ad agency Redpepper. The page aims to reduce the population in dog shelters. Mr. Reed told Fast Company

Every year we participate in an advertising industry event called Createathon where we donate work for nonprofits over the course of 24 hours … We stay up all night, and it is a blast. We also get very delirious, which is partly where this idea came from.

Mr. Reed says they also wanted to try and do something to bring some extra awareness to their cause.

We explored a few different ideas but kept coming back to doing something with [the open-source AI generative image algorithm] Stable Diffusion … Contrasting AI dogs versus real dogs seemed interesting.

Wags & WalksThis Dog Exists is designed to be simple. It displays a grid of four dogs; one of them is real, and the other three were created by the Stable Diffusion AI. FC reports that the team used Lexica.art—a generative image search engine—to find the perfect prompt for the cutest puppy creation. If you fail to guess the real dog 10 times, This Dog Exists displays a message that says,

Woof! It looks like you need a real dog because you don’t know what a real dog looks like 🙂

Good for dogs

While Stable Diffusion, DALL-E, and MidJourney still have problems creating believable human faces, Stable Diffusion seems to be pretty good at conjuring dogs. Except for a few imperfections, the fake dogs look pretty much like the real thing. 

This Dog Exists isn’t groundbreaking in its use of AI technology, but it is a cute and fun way to engage people. “Even if it only gets one extra dog adopted, I’ll consider it a success,” Mr. Reed concludes.

AI programs called generative adversarial networks, or GANs. GANs were designed by researcher Ian Goodfellow and his colleagues in the year 2014. They can learn to create fake images that are less and less distinguishable from real images, by pitting two neural networks against each other. Researchers says that artificial intelligence can create such realistic human faces that people can’t distinguish them from real faces – and they actually trust the fake faces more.

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Needless to say, the ability to generate realistic faces raises all kinds of ethical questions, even if they don’t belong to real humans. 

massive-scale machine learning systemsThese massive-scale machine learning systems can harm marginalized people through deeply embedded biases that can’t be easily engineered out. AI’s frequently create racist and sexist stereotypes.

While AI engineers say they’re doing their best to create safeguards that prevent abuse, it’s likely we’ve only just begun to see these large AI systems are capable of—and what types of harm they might cause.

 

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Ralph Bach has been in IT long enough to know better and has blogged from his Bach Seat about IT, careers, and anything else that catches his attention since 2005. You can follow him on LinkedInFacebook, and Twitter. Email the Bach Seat here.

Facial Recognition False Arrest

Facial Recognition False ArrestBack in January 2020, the Detroit Police Department arrested Robert Williams in his driveway in Farmington Hills according to The New York Times. He had his mug shot, fingerprints and DNA taken and was held overnight. Based on facial recognition software DPD decided that in October 2018 decided he had shoplifted 5 watches worth $3,800, from Shinola. Shinola is an upscale boutique that sells watches, bicycles, and leather goods in the trendy Midtown neighborhood of Detroit.

Detroit Police Department

Mr. Williams knew that he had not committed the crime in question. What he could not have known, as he sat under arrest, is that his case may be the first known account of an American being wrongfully arrested based on a flawed match from a facial recognition algorithm, according to experts on technology and the law. This is part of the systemic racial bias in law enforcement that millions are protesting. They are protesting not just the actions of individual officers, but bias in the systems used to monitor communities and identify people for prosecution.

Facial recognition systems have been used by police forces for more than two decades. Recent studies by MIT. and NIST (PDF), have found that while facial recognition technology works relatively well on white men, the results are less accurate for other demographics, in part because of a lack of diversity in the images used to develop the underlying databases.

Michigan State Police

As part of this debate, IBM, Amazon, and Microsoft paused new sales of facial recognition systems to  law enforcement. The gestures were largely symbolic, given that the companies are not big players in the industry. The technology police departments use, according to the NYT, is supplied by companies that aren’t household names, such as Vigilant Solutions, Cognitec, NEC, Rank One Computing, and Clearview AI.

Clare Garvie, a lawyer at Georgetown University’s Center on Privacy and Technology, has written about problems with the government’s use of facial recognition told the NYT she suspects Mr. Williams’ case is not the first case to misidentify someone to arrest them for a crime they didn’t commit. “This is just the first time we know about it.

facial recognitionMr. Williams’ case combines flawed technology with poor police work, illustrating how facial recognition can go awry according to the New York Times. The original still unsolved Shinola shoplifting case occurred in October 2018. Katherine Johnston, a loss prevention contractor for Shinola reviewed the store’s surveillance video and sent a copy to the Detroit police, according to the DPD report. Where it sat until the Michigan State Police got involved – in a shoplifting case.

In March 2019, Jennifer Coulson, a digital image examiner for the Michigan State Police, uploaded a “probe image” — a still from the Shinola video, showing a man in a red Cardinals cap — to the state’s facial recognition database. The DataWorks Plus system mapped the man’s face and searched for similar ones in a collection of 49 million photos.

Facail recognition is less accurate with people of color

Since 2005 Michigan’s facial recognition technology has been supplied by a South Carolina company called DataWorks Plus under a contract worth $5.5 million. The NYT says DataWorks Plus does not formally measure the systems’ accuracy or bias. Todd Pastorini, a DataWorks Plus general manager told the NYT, We’ve become a pseudo-expert in the technology.

In Michigan, the DataWorks facial recognition software used by the state police incorporates components developed by the Japanese tech giant NEC and by Rank One Computing, based in Colorado, according to Mr. Pastorini and a state police spokeswoman. In 2019, algorithms from both companies were included in a federal study of over 100 facial recognition systems that found they were biased, falsely identifying African-American and Asian faces 10 times to 100 times more than Caucasian faces.

I guess the computer got it wrong

After MSP’s Coulson, ran her search of the probe image, the system would have provided a row of results generated by NEC and a row from Rank One, along with confidence scores. Mr. Williams’s driver’s license photo was among the matches. Ms. Coulson sent it to the Detroit police as an “Investigative Lead Report.” 

Investigative Lead Report

This is what technology providers and law enforcement always emphasize when defending facial recognition, says the article:  It is only supposed to be a clue in the case, not a smoking gun. DPD Chief James Craig describes himself as a “strong believer”  in facial recognition software.

Collect evidenceBefore arresting Mr. Williams, investigators could have sought other evidence that he committed the theft, such as eyewitness testimony, location data from his phone, or proof that he owned the clothing that the suspect was wearing. In this case, however, according to the Detroit police report, investigators simply included Mr. Williams’s picture in a “6-pack photo lineup” they created and showed it to Shinola’s loss-prevention contractor, and she identified him. Shinola’s contractor. Johnston declined to comment.

Rank One’s chief executive, Brendan Klare, found fault with Ms. Johnston’s role in the process. “I am not sure if this qualifies them as an eyewitness, or gives their experience any more weight than other persons who may have viewed that same video after the fact.”  John Wise, a spokesman for NEC, told the author: A match using facial recognition alone is not a means for positive identification.

In Mr. Williams’s recollection, after he held the surveillance video still next to his face, the two detectives leaned back in their chairs and looked at one another. One detective, seeming chagrined, said to his partner: “I guess the computer got it wrong.” They turned over a third piece of paper, which was another photo of the man from the Shinola store next to Mr. Williams’s driver’s license. Mr. Williams again pointed out that they were not the same person.

Mr. Williams asked if he was free to go. “Unfortunately not,” one detective said. Mr. Williams was kept in custody for 30 hours, and released on a $1,000 personal bond. The Williams family contacted defense attorneys, most of whom, they said, assumed Mr. Williams was guilty of the crime and quoted prices of around $7,000 to represent him. They, also tweeted at the American Civil Liberties Union of Michigan, which took an immediate interest. said Phil Mayor, an attorney with the organization told the NYT:

American Civil Liberties Union of Michigan

We’ve been active in trying to sound the alarm bells around facial recognition, both as a threat to privacy when it works and a racist threat to everyone when it doesn’t,”  “We know these stories are out there, but they’re hard to hear about because people don’t usually realize they’ve been the victim of a bad facial recognition search.

Two weeks later, Mr. Williams appeared in a Wayne County court for an arraignment. When the case was called, the prosecutor moved to dismiss, but “without prejudice,” meaning Mr. Williams could later be charged again. Maria Miller, a spokeswoman for the prosecutor, said a second witness had been at the store in 2018 when the shoplifting occurred but had not been asked to look at a photo lineup. If the individual makes an identification in the future, she said, the office will decide whether to issue charges.

dismiss, but “without prejudice,” meaning he could later be charged againA DPD spokeswoman, Nicole Kirkwood, said that for now, the department “accepted the prosecutor’s decision to dismiss the case.” In a second statement to the NYT DPD doubled down saying it, “does not make arrests based solely on facial recognition. The investigator reviewed the video, interviewed witnesses, conducted a photo lineup.

The ACLU of Michigan filed a complaint with the city (PDF),  asking for an absolute dismissal of the case, an apology, and the removal of Mr. Williams’s information from Detroit’s criminal databases.

Mr. Williams’s lawyer, Victoria Burton-Harris, said that her client is “lucky,” despite what he went through. Ms. Burton-Harris said to the NYT

He is alive … He is a very large man. My experience has been, as a defense attorney, when officers interact with very large men, very large black men, they immediately act out of fear. They don’t know how to de-escalate a situation.

Mr. Williams had an alibi, had the Detroit police checked for one.

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MSP database has over 6 picture per adult in MichiganJust to celebrate Independence day – the Georgetown Law’s Center on Privacy and Technology says, at least a quarter of the nation’s law enforcement agencies have access to face recognition tools. The MSP database has almost 50 million pictures in it for about 8 million adults in Michigan. That is over 6 pictures per adult Michigander – many come from the Secretary of State when you get a driver’s license but undoubtedly many are scrapped from social media sites. Michigan is one of at least 16 states that allow the FBI to search its database of driver’s license photos.

While the MSP didn’t start using facial recognition technology until 2001, the Secretary of State’s Office has been giving State Police all its digital photos — without notice to motorists — since 1998.

DataWorks provides facial recognition systems to DPDDataWorks provides facial recognition systems to both DPD and MSP. The DPD two-year $1 million contract for the DataWorks Plus software is set to expire in July 2020. Detroit City Council President Brenda Jones told the Detroit News that the police department agreed to pull back its most recent request for a contract extension and conduct community outreach before seeking approval to extend the contract through Sept. 30, 2022.

Dan Korobkin, deputy legal director for the ACLU of Michigan points out that Civil rights icon Martin Luther King Jr. “was the target of massive FBI surveillance, under what was then the latest state-of-the-art technology.” In response, Robert Stevenson, executive director of the Michigan Association of Chiefs of Police and retired chief of the Livonia Police Department, told GovTech he believes most Michiganders trust the police, “We’ve evolved in the last 50 years, as a country, and as police agencies.” Well just ask George Floyd.

Stay safe out there!

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Ralph Bach has been in IT long enough to know better and has blogged from his Bach Seat about IT, careers, and anything else that catches his attention since 2005. You can follow him on LinkedInFacebook, and Twitter. Email the Bach Seat here.

VR You Can Taste

VR You Can TasteDuring the COIVD-19 lockdowns and social distancing, every generation has increased the use of their devices to inform and distract more than ever before. Wouldn’t it be great if our devices could encompass all of our senses? Well, that time is coming. Homei Miyashita a researcher at Meiji University in Japan has developed the Norimaki Synthesizer which can make the tongue sense taste without eating anything.

It was once thought that tongues had different regions for each taste.It was once thought that the tongue had different regions with concentrations of specific taste buds for each taste. Now we know that there are five basic tastes are sweet, sour (or acidic), salty, bitter, and umami. Bitter flavors are sharp, like coffee, unsweetened chocolate, or the peel of an orange or lemon. Umami is derived from the Japanese word for a pleasant savory taste, was added to the basic tastes group in 1990.

Taste buds have a chemical reaction to food

Taste buds have tiny openings that take in very small amounts of whatever we’re eating. Special “receptor cells” in the taste buds can then have a chemical reaction to the food, creating one of five basic tastes. The way these basic tastes combine creates the overall flavor of the food we’re eating.

SVCOnline explains a better understanding of how the tongue works is crucial to the new device. In order to trick your tongue, the device uses electrolytes inserted into five gels that trigger the five different tastes when they make contact with the human tongue. Gizmodo reports the color-coded gels, made from agar formed in the shape of long tubes to create tastes. The device uses:

The taste device

When the device is pressed against the tongue, the user experiences all five tastes at the same time. But, by using a small box with sliding controls the amount of different tastes can be lowered, creating different flavors. Sadly, it can’t produce the effect of spicy foods.

To create the different flavors the device is wrapped in copper foil so that when it’s held in hand and touched to the surface of the tongue, it forms an electrical circuit through the human body, facilitating a technique known as electrophoresis.

Electrophoresis is a process that moves molecules in a gel when an electrical current is applied. In this case, this process causes the ingredients in the agar tubes to move away from the tongue end of the tube, reducing the ability to taste them. It’s a subtractive process that selectively removes tastes to create a specific flavor profile – from gummy bears to sushi.

The device’s creator, Homei Miyashita, was inspired to create his “taste display” by experiments that proved our eyes can be tricked into seeing something that technically doesn’t exist. He wondered if the red, green, or blue pixels that make up the screens on your smartphone, PC, and TV could fool the eye, could he create something that could fool the tongue? Mr. Miyashita used a similar “pixel” approach o trick the tongue.

In his abstract, Professor Miyashita acknowledged the 2011 research of Hiromi Nakamura, who achieved “augmented gustation” by sending electrical charges through chopsticks, forks, and straws to create tastes humans could not perceive solely with their tongues.

Smell-O-Vision

Other inventors have tried to expand the senses for the media. In 1959, Charles Weiss, a public relations executive, created AromaRama. AromaRama distributed scents of horses, grass, exploding firecrackers, incense, and burning torches through the theater’s air-conditioning system during the first showing of “Behind the Great Wall.” But the NYT panned the movie, “Check off the novel experience as… a stunt. The artistic benefit of it is here demonstrated to be nil.”

Smell-O-VisionThe next year, inventor Hans Laube introduced an improved Smell-O-Vision with the movie “Scent of Mystery” which was augmented by smells such as freshly baked bread, wine, an ocean breeze, or a skunk delivered through beneath-the-seat tubes. Certain smells offered clues to imminent activity on the screen. But viewers complained of uneven or delayed distribution of smells, and the distracting noises of viewers struggling to sniff each scent. For fans and critics, the movie was a stinker. Famed comedian Henry Youngman quipped, “I didn’t understand the picture. I had a cold.

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It’s called a taste display because it was inspired by the way RGB pixels accumulate on a screen form an image of something that isn’t there. These electronic “taste pixels” can be manipulated to simulate any taste. Why? No idea. – But there will be an app for that too!

Stay safe out there!

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Ralph Bach has been in IT long enough to know better and has blogged from his Bach Seat about IT, careers, and anything else that catches his attention since 2005. You can follow him on LinkedInFacebook, and Twitter. Email the Bach Seat here.