Category Archives: Artificial Intelligence
Artificial Intelligence and Sexual Wellness: The Future is Looking (And Feeling) Good – Gizmodo Australia
What does artificial intelligence have to do with sex? No, its not a set up for a dirty joke. Its actually a question we recently asked the man in charge of tech at the worlds largest sexual wellness company.
When you think of technology and innovation while talking about sexual wellness devices (the term we prefer to use for sex toys), its likely you think of the speeds of a vibrator, or an app that controls something you use in the bedroom. But it goes much deeper than that. And the possibilities of where it can go in the future, thanks to tech such as artificial intelligence (AI), are as mind-blowing as an orgasm (at least for tech nerds like us).
The Lovehoney Group is on a mission to promote sexual happiness and empowerment through design, innovation and research and development. And after chatting with The Lovehoney Groups chief engineering and production officer Tobias Zegenhagen, its easy to see just how much tech is actually involved in the sexual wellness industry.
But what if it could go one step further? What if a device just knew what felt good? Enter AI.
Currently, the user or their partner is the one controlling certain buttons, either on the device or a remote control. But, what if the device could be the one controlling the device?
Algorithms, AI sensing your responses, then using that data in order to intelligently drive the toy the way you want it, Zegenhagen described of a future that isnt all that far away. An AI controlling a toy based on your movements, reactions and learning from the previous data its pulled from you.
You are getting information and you use that information intelligently in order to fulfil a user need.
Its pretty straight forward when its broken down like that.
Lovehoney Group has a product in the market already, the We-Vibe Chorus, which allows you to, via an app, share vibrations during sex. Chorus matches its vibration intensity to the strength of your grip, with the idea being that its completely in tune with you. The Chorus has a capacitive sensor in it that senses the act of sexual intercourse. During PIV sex, it senses the touching of the two bodies, and according to these touches, it controlls the toy.
It is a straightforward algorithm, Zegenhagen said.
It actually makes a lot of sense. If you think about each of the sexual partners youve had throughout your life, no ones body is the same.
How you move is individual and changes all the time from person to person, from day to day, Zegenhagen said, adding what you want during sex is also individual.
Controlling the toy in general, and then individualising it to the person. That is where I see AI coming in.
Theres an immense amount of promise. But its important Lovehoney Group (and their peers, of course) use technology for the right purpose. That is, not just using tech like AI for the sake of it, that it offers something of benefit to the sexual experience. And, that data privacy is front and centre.
It is definitely in our core to try to innovate, and we need to research in order to better understand user needs, and to use technology in order to advance and to innovate, Zegenhagen explained. But it isnt that straight forward. Theres an insane amount of people at Lovehoney Group in the R&D (research and development) space.
If you compare it with other technological fields or areas, what is real particular in this case, is that the requirements that you formulate are very blurry and very individual, he said. If you ask somebody, What does sexual fulfillment mean for you?, What is a perfect orgasm?, you could ask a hundred people and you get 500 answers.
Unlike with, say, a phone, when it comes to sexual wellness, its very difficult for a user to state the actual need. But as Zegenhagen explained, it is also very difficult to then verify that the need is actually being fulfilled by the technology. Thats without even taking into consideration any biological and neurological factors.
We have a rough understanding of how touch works and how we perceive stimulation, Zegenhagen said. But do we know all the mechanisms behind it? Absolutely not. What happens when I touch a rough surface with my hand? How do my mechanical receptors perceive that? How is that being transferred to the brain? All this is pretty much unclear.
While a sexual wellness device isnt the same as medication, the closest comparison is probably with developing a new drug. You answer a need, test it, tweak it, test on a broader audience but everyones response to that medication will be different.
The human being is too complex to fully understand, he added.
I think that the easiest technical solution to meet a user need is the best technical solution, not the most complex one.
You dont have to be technically complex to be innovative. You dont have to be technically complex to meet a user need it has to be as simple as possible.
Well, yes, thats true. It would definitely kill the mood if you had to read a 30-page user manual or learn something needed to be charged, paired, updated, etc the moment youre about to use it.
There is a huge playground for technology in our field, Zegenhagen said.
With AI offering all sorts of benefits to our sexual wellness, the future sure is looking (and feeling) good.
Doug Emhoff speaks to Holocaust survivor and his AI twin in LA – The Jewish News of Northern California
When Second Gentleman Douglas Emhoff sat down for a Zoom conversation with Holocaust survivor Pinchas Gutter on Wednesday, he opened by saying, I feel like I already know you!
Though the two had never met, Emhoff did, to an extent, know Gutter.
Just moments before the video call, Emhoff had engaged with Gutters interactive biography, asking him questions about his experience in concentration camps and even listening to Gutter sing Shir Hamaalot, the song that begins the blessing after meals.
Emhoff was at the University of Southern Californias Shoah Foundation, where he visited to explore the centers Dimensions in Testimony project, a series of artificial intelligence bots that allow people to interact in real time with survivors of the Holocaust and other genocides.
As a USC alum and the first Jewish vice presidential spouse, Emhoff knew the experience would be special overwhelming, even. But he said the exhibit far exceeds what I thought it was going to be.
Its so impressive, the use of the technology, Emhoff told the Jewish Telegraphic Agency. Its so real. And you really felt you were in the room you really felt you were talking to people. It was so engaging.
The visit was the latest in a series of Jewish events Emhoff has hosted and attended in his official capacity as the Second Gentleman andas a proud Jew.
I never expected my Jewish faith to be that big a deal in this role, he said. As it turned out, I was very wrong. And Im glad I was wrong, because it is a big deal.
Emhoff has baked matzah with Jewish day school students, helpedhost the first online Passover sederat the White House,hung a mezuzah at the vice presidents residence, and took part in festivities for Jewish American Heritage Month.
You see these young kids screaming when I walked into the room like I was some kind of rock star, Emhoff recalled with a laugh. You really see that this representation matters. And knowing that, I take it very seriously. I know this means a lot to a lot of people, as it does to me.
Emhoffs presence also meant a lot to the staff at the Shoah Foundation.
It was amazing, Kori Street, the organizations interim executive director, told JTA. For me, for the staff, for the university, to have someone of his stature, who understands the importance of what were doing here, who has a connection to the archive, it was so meaningful just in terms of how insightful he was and how much he got it. That doesnt always happen.
Street kicked off Emhoffs visit with an introduction to the center and its work. The institution is nearing its goal of reaching 10 million students globally each year, according to Street, and the AI initiative is a flagship product. The initiative, which the Shoah Foundation plans to make available through local Holocaust museums around the world, aims to ensure that the common practice of having survivors speak about their experiences can outlast the survivors themselves.
After showing Emhoff a video testimony of a Holocaust survivor from the same town as Emhoffs family in Eastern Europe, it was time to meet Gutter.
Emhoff spoke first with the AI rendering of Gutter, asking him a series of questions about his survival story, his message to students today, and yes, asking Gutter to sing him a song.
Thank you, Pinchas, Emhoff said to the screen with a smile. Ill see you in the other room.
There, real-life Gutter continued to share his story. He also expressed his gratitude to Emhoff and the Biden administration for their work combating hate and antisemitism.
I really feel that you are able to make a difference, and you are making a difference, Gutter told Emhoff.
Gutter spoke about the importance of sharing his story with younger generations and of connecting his experience with current events. He mentioned Russias war on Ukraine multiple times.
Take this flame, Gutter said he tells students. Light up the world with these flames and make the world a better place.
Emhoff was visibly moved by Gutters story. Both Gutters, in fact.
I love your message of unity, Emhoff told the real-life Gutter over Zoom. We all need to stand together and stand united against this epidemic of hate.
As he thinks about the challenges facing the American Jewish community, Emhoff said the words of the AI Gutter expressed exactly how Im feeling about these issues.
That AI message really rang true, Emhoff said. Hearing his positivity after everything hes been through all these memories that hes had to live with for so many years, 70-plus years and to be so positive, and so upbeat, and be willing to share with the world now through this technology, his story, is just really, its amazing.
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Doug Emhoff speaks to Holocaust survivor and his AI twin in LA - The Jewish News of Northern California
Oregon is dropping an artificial intelligence tool used in child welfare system – NPR
Sen. Ron Wyden, D-Ore., speaks during a Senate Finance Committee hearing on Oct. 19, 2021. Wyden says he has long been concerned about the algorithms used by his state's child welfare system. Mandel Ngan/AP hide caption
Sen. Ron Wyden, D-Ore., speaks during a Senate Finance Committee hearing on Oct. 19, 2021. Wyden says he has long been concerned about the algorithms used by his state's child welfare system.
Child welfare officials in Oregon will stop using an algorithm to help decide which families are investigated by social workers, opting instead for a new process that officials say will make better, more racially equitable decisions.
The move comes weeks after an Associated Press review of a separate algorithmic tool in Pennsylvania that had originally inspired Oregon officials to develop their model, and was found to have flagged a disproportionate number of Black children for "mandatory" neglect investigations when it first was in place.
Oregon's Department of Human Services announced to staff via email last month that after "extensive analysis" the agency's hotline workers would stop using the algorithm at the end of June to reduce disparities concerning which families are investigated for child abuse and neglect by child protective services.
"We are committed to continuous quality improvement and equity," Lacey Andresen, the agency's deputy director, said in the May 19 email.
Jake Sunderland, a department spokesman, said the existing algorithm would "no longer be necessary," since it can't be used with the state's new screening process. He declined to provide further details about why Oregon decided to replace the algorithm and would not elaborate on any related disparities that influenced the policy change.
Hotline workers' decisions about reports of child abuse and neglect mark a critical moment in the investigations process, when social workers first decide if families should face state intervention. The stakes are high not attending to an allegation could end with a child's death, but scrutinizing a family's life could set them up for separation.
From California to Colorado and Pennsylvania, as child welfare agencies use or consider implementing algorithms, an AP review identified concerns about transparency, reliability and racial disparities in the use of the technology, including their potential to harden bias in the child welfare system.
U.S. Sen. Ron Wyden, an Oregon Democrat, said he had long been concerned about the algorithms used by his state's child welfare system and reached out to the department again following the AP story to ask questions about racial bias a prevailing concern with the growing use of artificial intelligence tools in child protective services.
"Making decisions about what should happen to children and families is far too important a task to give untested algorithms," Wyden said in a statement. "I'm glad the Oregon Department of Human Services is taking the concerns I raised about racial bias seriously and is pausing the use of its screening tool."
Sunderland said Oregon child welfare officials had long been considering changing their investigations process before making the announcement last month.
He added that the state decided recently that the algorithm would be completely replaced by its new program, called the Structured Decision Making model, which aligns with many other child welfare jurisdictions across the country.
Oregon's Safety at Screening Tool was inspired by the influential Allegheny Family Screening Tool, which is named for the county surrounding Pittsburgh, and is aimed at predicting the risk that children face of winding up in foster care or being investigated in the future. It was first implemented in 2018. Social workers view the numerical risk scores the algorithm generates the higher the number, the greater the risk as they decide if a different social worker should go out to investigate the family.
But Oregon officials tweaked their original algorithm to only draw from internal child welfare data in calculating a family's risk, and tried to deliberately address racial bias in its design with a "fairness correction."
In response to Carnegie Mellon University researchers' findings that Allegheny County's algorithm initially flagged a disproportionate number of Black families for "mandatory" child neglect investigations, county officials called the research "hypothetical," and noted that social workers can always override the tool, which was never intended to be used on its own.
Wyden is a chief sponsor of a bill that seeks to establish transparency and national oversight of software, algorithms and other automated systems.
"With the livelihoods and safety of children and families at stake, technology used by the state must be equitable and I will continue to watchdog," Wyden said.
The second tool that Oregon developed an algorithm to help decide when foster care children can be reunified with their families remains on hiatus as researchers rework the model. Sunderland said the pilot was paused months ago due to inadequate data but that there is "no expectation that it will be unpaused soon."
In recent years while under scrutiny by a crisis oversight board ordered by the governor, the state agency currently preparing to hire its eighth new child welfare director in six years considered three additional algorithms, including predictive models that sought to assess a child's risk for death and severe injury, whether children should be placed in foster care, and if so, where. Sunderland said the child welfare department never built those tools, however.
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Oregon is dropping an artificial intelligence tool used in child welfare system - NPR
Artificial intelligence spotted inventing its own creepy language – New York Post
An artificial intelligence program has developed its own language and no one can understand it.
OpenAI is anartificial intelligencesystems developer their programs are fantastic examples of super-computing but there are quirks.
DALLE-E2 isOpenAIs latest AI system it can generate realistic or artistic images from user-entered text descriptions.
DALLE-E2 represents a milestone in machine learning OpenAIs site says the program learned the relationship between images and the text used to describe them.
A DALLE-E2 demonstration includesinteractive keywordsfor visiting users to play with and generate images toggling different keywords will result in different images, styles, and subjects.
But the system has one strange behavior itswritingits own language of random arrangements of letters, and researchers dont know why.
Giannis Daras, a computer science Ph.D. student at the University of Texas, published aTwitter threaddetailing DALLE-E2s unexplained new language.
Daras told DALLE-E2 to create an image of farmers talking about vegetables and the program did so, but the farmers speech read vicootes some unknown AI word.
Darasfedvicootes back into the DALLE-E2 system and got back pictures of vegetables.
We then feed the words: Apoploe vesrreaitars and we get birds. Daras wrote on Twitter.
It seems that the farmers are talking about birds, messing with their vegetables!
Stay up on the very latest with Evening Update.
Daras and a co-author have written apaperon DALLE-E2s hidden vocabulary.
They acknowledge that telling DALLE-E2 to generate images of words the command an image of the word airplane is Daras example normally results in DALLE-E2 spitting out gibberish text.
When plugged back into DALLE-E2, that gibberish text will result in images of airplanes which says something about the way DALLE-E2 talks to and thinks of itself.
Some AI researchers argued that DALLE-E2s gibberish text is random noise.
Hopefully, we dont come to find the DALLE-E2s second language was a security flaw that needed patching after its too late.
This article originally appeared onThe Sunand was reproduced here with permission.
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Artificial intelligence spotted inventing its own creepy language - New York Post
This Artificial Intelligence Stock Has a $596 Billion Opportunity – The Motley Fool
No technology has ever had the potential to transform the way the world does business quite like artificial intelligence (AI). Even in its early stages, it's already proving its ability to complete complex tasks in a fraction of the time that humans can, with adoption in both large organizations and small-scale start-ups accelerating.
C3.ai (AI -4.13%) is the world's first enterprise AI provider. It sells ready-made and customized applications to companies that want to leverage the power of this advanced technology without having to build it from scratch, and its customer base continues to grow in both number and pedigree.
C3.ai just reported its full-year results for fiscal 2022 (ended April 30), and beyond its strong financial growth, the company also revealed the magnitude of its future opportunity.
Image source: Getty Images.
Sentiment among both investors and the general public continues to trend against fossil fuel companies as people become more conscious about humanity's impact on the environment. Oil and gas companies are constantly trying to improve their processes to produce cleaner energy, and artificial intelligence is now helping them do that.
C3.ai serves companies in 11 industries, but 54% of its revenue comes from the fossil fuel sector. The company has a long-standing partnership with oil and gas services giant Baker Hughes (BKR -0.65%). Together, they've developed a full suite of applications designed to enable the industry to predict catastrophic equipment failures and to help reduce carbon emissions. Shell (SHEL 0.67%), for example, uses C3.ai's software to monitor 10,692 pieces of equipment every single day, ingesting data from over 1.1 million sensors to make 515 million predictions each month.
C3.ai continues to report major customer wins. It just received its first two orders as part of a five-year, $500 million deal with the U.S. Department of Defense, which was signed last quarter. And its collaborations with the world's largest cloud services providers, like Alphabet's Google Cloud, have delivered further blockbuster signings like Tyson Foodsand United Parcel Service. C3.ai and Google Cloud are leaning on each other's expertise to make advanced AI tools more accessible for a growing list of industries.
Overall, by the numbers, C3.ai's customer count is proof of steady demand.
C3.ai reported revenue of $72.3 million in the fourth quarter, which was a 38% year-over-year jump. For the full year, it met its previous guidance and delivered $252.8 million, which was also 38% higher compared to 2021.
But the company's remaining performance obligations (RPO) will likely capture the attention of investors because they increased by a whopping 62% to $477 million. It's an important number to track because it's effectively a looking glass into the future, as C3.ai expects RPO will eventually convert into revenue.
C3.ai isn't a profitable company just yet. It made a net loss of $192 million for its 2022 full year, a sizable jump from the $55 million it lost in 2021, mainly because it more than doubled its investment in research and development and increased its sales and marketing expenditure by nearly $80 million.
But since the company maintains a gross profit margin of around 75%, it has the flexibility to rein in its operating costs in the future to improve its bottom-line results. C3.ai is deliberately choosing to sacrifice profitability to invest heavily in growth because it's chasing an addressable market it believes will be worth $596 billion by 2025.
C3.ai maintains an extremely strong financial position, with over $950 million in cash and equivalents on its balance sheet. That means the company could operate at its 2022 loss rate of $192 million for the next five years before it runs out of cash, leaving plenty of time to add growth before working toward profitability.
Unfortunately, the current market environment has been unfavorable to loss-making technology companies. The Nasdaq 100 tech index currently trades in a bear market, having declined by 25% from its all-time high. It's representative of dampened sentiment thanks to rising interest rates and geopolitical tensions, which have forced investors to reprice their growth expectations.
C3.ai stock was having difficulties prior to this period, as growth hasn't been quite as strong as some early backers expected. Overall, the stock price has fallen by 87% since logging its all-time high of $161 per share shortly after its initial public offering in December 2020.
But that might be a great opportunity for investors with a long-term time horizon. C3.ai has some of the world's largest companies on its customer list, it's running a healthy gross profit margin, and it's staring at a $596 billion opportunity in one of the most exciting areas of the technology sector right now.
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This Artificial Intelligence Stock Has a $596 Billion Opportunity - The Motley Fool
Researchers urged to use Artificial Intelligence to find solutions of problems in medical field – Telangana Today
Published: Published Date - 04:53 PM, Mon - 6 June 22
Warangal: Kakatiya Medical College Principal Dr Divvela Mohandas has urged the researchers and faculty members of the computer science engineering (CSE) to find solutions to the real-life problems in the field of medicine for the benefit of the patients. He said that the latest technologies like, Artificial Intelligence(AI), image processing, Machine Learning (ML), Deep Learning (DL), robotics, and Data Science are playing crucial roles in the field of medicine as they are very useful in diagnosing the health issues through CT scan, MRI, ECG, etc., and treatment.
Addressing the inaugural ceremony of the faulty development programme (FD) on Artificial Intelligence for Computer Vision and Image Processing organised at the Kakatiya Institute of Technology and Science, here on Monday, Mohandas said that the advanced technologies like AI, ML and robotics would give accurate output. You must keep abreast of the latest technologies and meet the needs of the ever-changing industry, he said. He, however, said that no technology replaces a doctor or a teacher.
Forensic Medicine Professor in Prathima Institute of Medical Sciences, Karimnagar, Dr TKK Naidu, who delivered a keynote address said that smart transportation systems using artificial intelligence would avoid accidents and save human lives. FDP coordinator Prof T Kishore Kumar said that they are working on the India Science and Engineering Research Board (SERB) project on application of AI & IOT for designing portable knee joint healthcare monitoring systems worth Rs 40 lakh. He along with others including the faculty of NITW submitted a proposal for a DST project worth Rs 1.50 crore, he added.
The FDP aims at deliberating various AI & ML algorithms and research strategies to be adopted for effective and efficient processing of medical images through computer vision. This workshop allows collaborations between AI researchers and health practitioners to discuss socio-technological challenges and come up with state-of-the-art technology directions in the interdisciplinary field of engineering and medicine. KITS Principal Prof K Ashoka Reddy said that the FDP would help to get the medical and engineering fields closer to solve real time problems using Artificial Intelligence. This FDP is a good start up concept for National Educational Policy (NEP) 2020. The participants of this FDP are from NIT Warangal and KITSW, IITs/NITs/IIITs and industries.
Academicians in the concerned field from IITs/NITs/IIITs have been invited to deliver lectures during the two weeks. 60 participants were shortlisted from numerous applicants, he added. FDP incharge Dr V Shankar, FDP Co-coordinator, Dr A Jothi Prabha Dr S Narsimha Reddy, Dr C Srinivas, Associate Professor Dr D Prabhakara Chary, and others were present.
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Researchers urged to use Artificial Intelligence to find solutions of problems in medical field - Telangana Today
Curation of the Entire Human Genome Requires the Best of Both Human and Artificial Intelligence – Technology Networks
The following article is an opinion piece written by Mark J. Kiel. The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position of Technology Networks.
The recent publication of the gapless, telomere-to-telomere human genome assembly serves as a real reminder of the significant work that remained to be completed from initial draft genome to the final sequence assembly. Similarly, while we have learned much about causative genetic variants in human disease over the past many years, there is much work that remains to complete this knowledge and to put it into practice.
To fully realize the promise of precision medicine, it is my contention that we must pre-curate every variant in the human genome. It is not scalable for analysts in clinical practice to spend as much as 90 minutes per variant to report the results of a molecular lab test. Pre-curation will make this analysis maximally efficient and reproducible.
A great example of where pre-curation will be beneficial is newborn screening by next-generation sequencing. This new method of screening demands a great deal of information about a multitude of diseases to ensure the utmost accuracy of resulting diagnoses. However, real-time assessment of this information for each patient and each variant will challenge the scalability of this initiative.
Conventional methods for variant curation are laborious, slow, incomplete and error-prone relying as they do on painstaking manual searches for evidence in the scientific and clinical literature. These manual processes too often miss key data and lead to inaccurate conclusions about the clinical significance of a patients variant. Collectively, all of this previous work has led to the pre-curation of just a fraction of human genetic variants. Moreover, these older pre-curations are often inadequate as new knowledge is being created every day requiring continuous updates to existing curations to ensure nothing is missed. If we continue to rely on outmoded techniques, it will not be possible to fully curate the human genome in our lifetimes.
Faster and more comprehensive variant curation will require a combinatorial approach merging the scalability and sensitivity of AI and the specificity and accuracy that can only come from the expert judgment of experienced human curators. AI-driven indexing of the scientific and clinical literature can ensure more complete information for each variant, while AI-informed expert curation delivers maximum specificity for results in a maximally efficient manner.
The primary bottleneck to achieving accurate and comprehensive variant curation is the need to manually locate, assess, annotate and document evidence from the scientific and clinical literature. In particular, the nuances of the genetic code and the idiosyncrasies of genetic nomenclature and other complexities of biology make it difficult to disambiguate terminology and ensure that curations are correct and complete.
AI is a natural solution to these challenges. Only computational approaches can meet the scale and sensitivity requirements of this ambitious genome-wide variant curation. There is precedent for using AI to index vast amounts of data often unstructured and poorly organized data so it is an excellent fit for indexing the scientific and clinical literature. Paying attention to and resolving genetic ambiguities and focusing on the most critical clinical information is paramount.
A team of highly trained experts is necessary to carefully assess the assembled evidence and make an informed judgment about its appropriateness and applicability, as well as ensure the utmost accuracy of all final interpretations. This review process can be further accelerated by AI-driven organization and annotation of the data.
This approach is already making it possible to deliver new insights about disease-causing variants in patients. In one example, scientists at the Rare Genomics Institute reanalyzed previously inconclusive exome results using an AI-powered tool and found a single scientific report that allowed them to classify a key variant as pathogenic and produce an evidence-based diagnosis and effective treatment for the patient.
With the speed and scale afforded by AI technology, it will be possible within the next several years to curate the entire human genome. With a combinatorial approach that brings together the best of automated AI and expert curation, we can firmly establish the foundation of genomic intelligence needed to make precision medicine a reality for all patients.
About the author:
Mark Kiel is chief scientific officer and co-founder of Genomenon, an AI genomics company. He has extensive experience in genome sequencing and clinical data analysis. Mark is a molecular genetic pathologist having received his MD/PhD in stem cell biology and cancer genomics from the University of Michigan.
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Curation of the Entire Human Genome Requires the Best of Both Human and Artificial Intelligence - Technology Networks
Evaluating brain MRI scans with the help of artificial intelligence – MIT Technology Review
Greece is just one example of a population where the share of older people is expanding, and with it the incidences of neurodegenerative diseases. Among these, Alzheimers disease is the most prevalent, accounting for 70% of neurodegenerative disease cases in Greece. According to estimates published by the Alzheimer Society of Greece, 197,000 people are suffering from the disease at present. This number is expected to rise to 354,000 by 2050.
Dr. Andreas Papadopoulos1, a physician and scientific coordinator at Iatropolis Medical Group, a leading diagnostic provider near Athens, Greece, explains the key role of early diagnosis: The likelihood of developing Alzheimers may be only 1% to 2% at age 65. But then it doubles every five years. Existing drugs cannot reverse the course of the degeneration; they can only slow it down. This is why its crucial to make the right diagnosis in the preliminary stageswhen the first mild cognitive disorder appearsand to filter out Alzheimers patients2.
Diseases like Alzheimers or other neurodegenerative pathologies characteristically have a very slow progression, which makes is difficult to recognize and quantify pathological changes on brain MRI images at an early stage. In evaluating scans, some radiologists describe the process as one of guesstimation, as visual changes in the highly complex anatomy of the brain are not always possible to observe well with the human eye. This is where technical innovations such as artificial intelligence can offer support in interpreting clinical images.
One such tool is the AI-Rad Companion Brain MR3. Part of a family of AI-based, decision-support solutions for imaging, AI-Rad Companion Brain MR is a brain volumetry software that provides automatic volumetric quantification of different brain segments. It is able to segment them from each other: it isolates the hippocampi and the lobes of the brain and quantifies white matter and gray matter volumes for each segment individually. says Dr. Papadopoulos. In total, it has the capacity to segment, measure volumes, and highlight more than 40 regions of the brain.
Calculating volumetric properties manually can be an extremely laborious and time-consuming task. More importantly, it also involves a degree of precise observation that humans are simply not able to achieve. says Dr. Papadopoulos. Papadopoulos has always been an early adopter and welcomed technological innovations in imaging throughout his career. This AI-powered tool means that he can now also compare the quantifications with normative data from a healthy population. And its not all about the automation: the software displays the data in a structured report and generates a highlighted deviation map based on user settings. This allows the user to also monitor volumetric changes manually with all the key data prepared automatically in advance.
Opportunities for more accurate observation and evaluation of volumetric changes in the brain encourages Papadopoulos when he considers how important the early detection of neurodegenerative diseases is. He explains: In the early stages, the volumetric changes are small. In the hippocampus, for example, there is a volume reduction of 10% to 15%, which is very difficult for the eye to detect. But the objective calculations provided by the system could prove a big help.
The aim of AI is to relieve physicians of a considerable burden and, ultimately, to save time when optimally embedded in the workflow. An extremely valuable role for this particular AI-powered postprocessing tool is that it can visualize a deviation of the different structures that might be hard to identify with the naked eye. Papadopoulos already recognizes that the greatest advantage in his work is the objective framework that AI-Rad Companion Brain MR provides on which he can base his subjective assessment during an examination.
AI-Rad Companion4 from Siemens Healthineers supports clinicians in their daily routine of diagnostic decision-making. To maintain a continuous value stream, our AI-powered tools include regular software updates and upgrades that are deployed to the customers via the cloud. Customers can decide whether they want to integrate a fully cloud-based approach into their working environment leveraging all the benefits of the cloud or a hybrid approach that allows them to process imaging data within their own hospital IT setup.
The upcoming software version of AI-Rad Companion Brain MR will contain new algorithms that are capable of segmenting, quantifying, and visualizing white matter hyperintensities (WMH). Along with the McDonald criteria, reporting WHM aids in multiple sclerosis (MS) evaluation.
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Evaluating brain MRI scans with the help of artificial intelligence - MIT Technology Review
Global Artificial Intelligence In Life Sciences Market To be Driven by the High Demand For AI Solutions in The Forecast Period Of 2022-2027 – Digital…
The new report by Expert Market Research titled, GlobalArtificial Intelligence in Life Sciences MarketReport and Forecast 2022-2027, givesanin-depth analysis of theglobal artificial intelligence in life sciences market, assessing the market based on its segments like applications andmajor regions. The report tracks the latest trends in the industry and studies their impact on the overall market. It also assessesthe market dynamics, covering the key demand and price indicators, along withanalysingthe market based on the SWOT and Porters Five Forces models.
Get a Free Sample Report with Table of Contents https://bit.ly/3Mg5iTe
The keyhighlights of the report include:
Market Overview (2017-2027)
Forecast CAGR (2022-2027):28.7%
The amount of health and omics-related data created and stored has increased dramatically in recent years. While tech companies like Google, Apple, and Amazon have been using artificial intelligence (AI) for years, its usage in life sciences and big pharma, particularly biomedicine and healthcare, has been growing. AI has aided in the collection of patient and clinical trial data for medication development and repurposing; in clinical trials, patient data can be gathered in real-time and evaluated using AI techniques. Mobile technologies linked to AI are increasingly used to improve patients lives. Researchers use the potential of machines to improve diagnoses with the help of imaging in multiple medical specialities, including dermatology, radiology, pathology, and ophthalmology. Such factors are expected to boost the global market growth.
Industry Definition and Major Segments
The analysis of small systems-of-interest specialised datasets, an emerging topic of artificial intelligence (AI), can be used to improve drug discovery and personalised medicine. Artificial intelligence in the life sciences has the potential to improve the health-care system, particularly customised treatment, and drug discovery.
Read Full Report with Table of Contents https://bit.ly/3GVoQel
By application, the market is segmented into:
Medical Diagnosis Biotechnology Drug Discovery Precision and Personalised Medicine Clinical Trials Patient Monitoring
On the basis ofregion, themarket is segmentedinto:
North America Europe Asia Pacific Latin America Middle East andAfrica
Market Trends
Advancements in AI have enabled the completion of several tasks in radiological imaging, including risk assessment, diagnosis, prognosis, and response to various medicines, along with the discovery of diseases using a variety of omics technologies. AI platforms have the potential to access digitised patient health records and recommend the best treatment plan. Also, through continuous monitoring of multiple parameters, AI may advise doctors to adjust doses or, in the event of a change in symptoms, to update the current treatment and replace it with a more effective alternative. With the rise of cyber threats and the evasion of signature-based systems, smart cyber solutions are becoming more important to protect the enormous volumes of data that biopharma businesses control and have access to. AI-based approaches could help cybersecurity specialists by improving threat intelligence and prediction, as well as enabling faster attack detection and response. These characteristics are propelling the market growth globally.
Key Market Players
The major players in the marketare IBM Corporation, NuMedii Inc., Atomwise Inc, AiCure LLC, and Nuance Communications Inc., among others. Thereport covers the market shares, capacities, plant turnarounds, expansions, investments and mergers and acquisitions, among other latest developments of these market players.
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Global Artificial Intelligence In Life Sciences Market To be Driven by the High Demand For AI Solutions in The Forecast Period Of 2022-2027 - Digital...
4 skills that won’t be replaced by Artificial Intelligence (AI) in the future – Kalinga TV
New Delhi: Youve probably heard for years that the workforce would be supplanted by robots. AI has changed several roles, such as using self-checkouts, ATMs, and customer support chatbots. The goal is not to scare people, but to highlight the fact that AI is constantly altering lives and executing activities to replace the human workforce. At the same time, technological advancements are producing new career prospects. AI is predicted to increase the demand for professionals, particularly in robotics and software engineering. As a result, AI has the potential to eliminate millions of current occupations while also creating millions of new ones.
Among the many concerns that AI raises is the possibility of wiping out a large portion of the human workforce by eliminating the need for manual labour. But it will simultaneously liberate humans from having to perform tedious, repetitive tasks, allowing them to focus on more complex and rewarding projects, or simply take some much-needed time off.
According to a McKinsey report, depending on the adoption scenario, automation will displace between 400 and 800 million jobs by 2030, requiring up to 375 million people to change job categories entirely.
These figures can make people feel uneasy and anxious about the future. However, history suggests that this may not be the case; there is no question that some industries will be transformed to the point where they no longer require human labour, leading toward job redefinition and business process reform. For eg, the diagnosis of many health issues could be effectively automated, making doctors focus on other major issues that need their attention. In terms of replacing humans completely, human labour is and will continue to be necessary for the foreseeable future.
Though the potential of AI is unimaginable it is also restricted. While it is apparent that AI will dominate the professional world on many levels. However, there can be no denial that as advanced as AI may be, it can and never will be able to replicate human consciousness that reinforces the human beings position at the top of the food chain.
Until now, we are talking about the jobs that can be snatched as technology advances but then, the human aspects of work cannot be replaced. Lets focus on something that they cannot do. There are some jobs that only humans are capable of performing.
There are jobs that require creation, conceptualization, complex strategic planning, and dealing with unknown spaces and feelings or emotional interactions that are way beyond the expertise of an AI as of now. Lets now talk about certain skills that are irreplaceable till the human race exist.
1. Empathy is unique to humans: Some may argue that animals show empathy as well, but they are not the ones taking over the jobs. Humans, unlike programmed software designed to produce a specific result, are capable of feeling emotions. It may seem contradictory, but the personal affinity between a person and an organisation is the foundation of a professional relationship. Humans need a personal connection that extends beyond the professional realm to develop trust and human connection, something that bot technology completely lacks.
2. Emotional Intelligence: Though accurate, the AI is not intuitive, or culturally sensitive because thats a human trait. No matter how accurately it is programmed to carry out a task, it cannot possess the human ability to adjust to the algorithm of human intellect. For instance, reading into the situation or the face of another human. It lacks emotional intellect which makes humans capable of understanding and handling an interaction that needs emotional communication. Exactly during your customer care service, one would always prefer a human interaction to read and understand the situation than an automated machine that cannot work or help beyond the programming.
3. Creativity: Perk of being human: AI can improve productivity and efficiency by reducing errors and repetition and replacing manual jobs with intelligent automated solutions, but it cannot comprehend human psychology. Furthermore, as the world becomes more AI-enabled, humans will be able to take on increasingly innovative tasks.
4. Problem-solving outside a code: Humans can deal with unexpected uncertainty by analysing the situation; like critical thinking during complex scenarios, and adopting creative tactics. Unlike humans, who may function under a variety of obstacles and settings, AI-powered devices cannot perform beyond their function, may be far in the future but not in the foreseeable one.
There is not even the slightest doubt that AI will not drive the future. To make AI work, humans need to be creative, insightful, and contextually aware. The reason for this is straightforward: humans will continue to provide value that machines cannot duplicate.
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4 skills that won't be replaced by Artificial Intelligence (AI) in the future - Kalinga TV