Visum Technologiesis in the Online Photos Industry

Visum Technologies

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बिडेन की तकनीकी नीतियों का लक्ष्य मानव अधिकारों की रक्षा करना है

バイデンのテクノロジー政策はいかにして人権保護を目指すのか

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Como as políticas tecnológicas de Biden visam proteger os direitos humanos

Как техническая политика Байдена направлена на защиту прав человека

Biden'ın Teknoloji Politikaları İnsan Haklarını Nasıl Korumayı Amaçlıyor?

Các chính sách công nghệ của Biden nhằm mục đích bảo vệ nhân quyền như thế nào

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This paper is available on arxiv under CC 4.0 license. Authors: (1) Muzhaffar Hazman, University of Galway, Ireland; (2) Susan McKeever, Technological University Dublin, Ireland; (3) Josephine Griffith, University of Galway, Ireland. Table of Links Abstract and Introduction Related Works Methodology Results Limitations and Future Works Conclusion, Acknowledgments, and References A Hyperparameters and Settings B Metric: Weighted F1-Score C Architectural Details D Performance Benchmarking E Contingency Table: Baseline vs. Text-STILT 6 Conclusion In this work, we addressed the challenge of training multimodal meme sentiment classifiers on a limited number of labelled memes by incorporating unimodal sentiment analysis data. We did so by proposing the first instance of STILT that applies unimodal intermediate tasks to a multimodal target task. Specifically, we tested image-only and text-only sentiment classification as intermediate tasks in training a meme sentiment classifier. We showed that this approach worked – unimodal text improved meme classification performance to a statistically significant degree. This novel approach allowed us to train a meme classifier that outperforms meme-only finetuning with only 60% as many labelled meme samples. As possible explanations for our observations, we discuss apparent similarities and differences in the roles of image and text modalities between unimodal and multimodal sentiment analysis tasks. Acknowledgments This work was conducted with the financial support of the Science Foundation Ireland Centre for Research Training in Digitally-Enhanced Reality (d-real) under Grant No. 18/CRT/6224; and the provision of computational facilities and support from the Irish Centre for High-End Computing (ICHEC). References Christian Bauckhage. 2011. Insights into internet memes. Proceedings of the International AAAI Conference on Web and Social Media, 5(1):42–49. Efrat Blaier, Itzik Malkiel, and Lior Wolf. 2021. 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Innovative Strategies in Meme Sentiment Analysis: The Impact of Unimodal Training

This paper is under CC 4.0 license. available on arxiv Authors: (1) Shreyash Mishra has an equal contribution from IIIT Sri City, India; (2) S Suryavardan has an equal contribution from IIIT Sri City, India; (3) Megha Chakraborty, University of South Carolina, USA; (4) Parth Patwa, UCLA, USA; (5) Anku Rani, University of South Carolina, USA; (6) Aman Chadha, work does not relate to a position at Amazon from Stanford University, USA, or Amazon AI, USA; (7) Aishwarya Reganti, CMU, USA; (8) Amitava Das, University of South Carolina, USA; (9) Amit Sheth, University of South Carolina, USA; (10) Manoj Chinnakotla, Microsoft, USA; (11) Asif Ekbal, IIT Patna, India; (12) Srijan Kumar, Georgia Tech, USA. Table of Links Abstract & Introduction Related Work Task Details Participating systems Results Conclusion and Future Work and References 6. Conclusion and Future Work In this paper, we summarize the approaches used by the participants for the Memotion 3 task and analyze the results. Due to the multi-modal nature of the dataset, all teams use a pre-trained image and text embedding models. However, each team presents a novel model pipeline. The highest scores achieved in Task A, Task B and Task C of Memotion 3.0 are 34.41%, 79.77% and 59.82% respectively, which shows there is significant room for improvement. On analysis of the results and the mis-classified examples on the test set, we find that "Sarcasm" and "Humour" are difficult to identify, especially in code-mixed memes. While we address Hind-English code-mixed memes in this paper, future work could include exploring other languages/language pairs. A unified baseline model to analyze memes in multiple languages could also be an interesting possibility. References [1] R. Dawkins, The selfish gene, Granada Publishing Lim, 1979. [2] A. Marwick, Memes, Contexts 12 (2013) 12–13. [3] N. Akhther, Internet memes as form of cultural discourse: A rhetorical analysis on facebook, 2018. doi:10.31234/osf.io/sx6t7. [4] S. 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Ekbal, et al., Memotion 2: Dataset on sentiment and emotion analysis of memes, in: Proceedings of De-Factify: Workshop on Multimodal Fact Checking and Hate Speech Detection, 2022. [60] K. N. Phan, G.-S. Lee, H.-J. Yang, S.-H. Kim, Little flower at memotion 2.0 2022: Ensemble of multi-modal model using attention mechanism in memotion analysis, in: Proceedings of De-Factify: Workshop on Multimodal Fact Checking and Hate Speech Detection, 2022. [61] T. Morishita, G. Morio, S. Horiguchi, H. Ozaki, T. Miyoshi, Hitachi at SemEval-2020 task 8: Simple but effective modality ensemble for meme emotion recognition, in: SemEval, 2020. [62] Y. Guo, J. Huang, Y. Dong, M. Xu, Guoym at SemEval-2020 task 8: Ensemble-based classification of visuo-lingual metaphor in memes, in: SemEval, 2020. [63] G.-A. Vlad, G.-E. Zaharia, D.-C. Cercel, et al., Upb at semeval-2020 task 8: Joint textual and visual modeling in a multi-task learning architecture for memotion analysis, 2020. arXiv:2009.02779. [64] T. T. Nguyen, N. T. Pham, N. D. Nguyen, et al., Hcilab at memotion 2.0 2022: Analysis of sentiment, emotion and intensity of emotion classes from meme images using single and multi modalities, in: Proceedings of De-Factify: Workshop on Multimodal Fact Checking and Hate Speech Detection, 2022. [65] G. G. Lee, M. Shen, Amazon pars at memotion 2.0 2022: Multi-modal multi-task learning for memotion 2.0 challenge, Proceedings of De-Factify: Workshop on Multimodal Fact Checking and Hate Speech Detection (2020). [66] M. Bhange, N. Kasliwal, Hinglishnlp: Fine-tuned language models for hinglish sentiment detection, arXiv preprint arXiv:2008.09820 (2020). [67] A. Dosovitskiy, L. Beyer, A. Kolesnikov, et al., An image is worth 16x16 words: Transformers for image recognition at scale, arXiv:2010.11929 (2020). [68] W. Yu, D. Kolossa, wentaorub at Memotion 3: Ensemble learning for multi-modal meme classification, in: Proceedings of De-Factify 2: Workshop on Multimodal Fact Checking and Hate Speech Detection, CEUR, 2023. [69] A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, et al., Learning transferable visual models from natural language supervision, in: ICML, 2021. [70] X. Li, X. Yin, C. Li, P. Zhang, et al., Oscar: Object-semantics aligned pre-training for vision-language tasks, 2020. arXiv:2004.06165. [71] Y.-C. Tang, K.-D. Wang, T.-Y. Ou, W.-C. Peng, NYCU_TWO at Memotion 3: Good foundation, good teacher, then you have good meme analysis, in: Proceedings of De-Factify 2: Workshop on Multimodal Fact Checking and Hate Speech Detection, CEUR, 2023. [72] Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, B. Guo, Swin transformer: Hierarchical vision transformer using shifted windows, 2021. arXiv:2103.14030. [73] X. Guo, J. Ma, A. Zubiaga, NUAA-QMUL-AIIT at Memotion 3: Multi-modal fusion with squeeze-and-excitation for internet meme emotion analysis, in: Proceedings of De-Factify 2: Workshop on Multimodal Fact Checking and Hate Speech Detection, CEUR, 2023. [74] Y. Liu, M. Ott, N. Goyal, J. Du, M. Joshi, D. Chen, O. Levy, M. Lewis, L. Zettlemoyer, V. Stoyanov, Roberta: A robustly optimized bert pretraining approach (2019). [75] X. Zhai, J. Puigcerver, A. Kolesnikov, et al., A large-scale study of representation learning with the visual task adaptation benchmark, 2020. arXiv:1910.04867. [76] G. Ke, Q. Meng, T. Finley, et al., Lightgbm: A highly efficient gradient boosting decision tree, in: Neurips, 2017. [77] K. He, X. Zhang, S. Ren, J. Sun, Deep residual learning for image recognition, in: CVPR, 2016. [78] F. Schroff, D. Kalenichenko, J. Philbin, FaceNet: A unified embedding for face recognition and clustering, in: CVPR, 2015.

Overview of Memotion 3: Sentiment & Emotion
Analysis of Codemixed Hinglish - Conclusion

Apparently not satisfied with handing over the power of generative AI to the masses, both Google and OpenAI are now looking to further commercialize their technologies by targeting the big fish. Just recently, Google and OpenAI announced that they would be offering a version of their generative AI tools tailored for enterprise customers. In Google's case, the company is playing catch up with Microsoft after fumbling its big generative AI reveal via Bard. Microsoft has had a big lead over Google, having initially invested in OpenAI back when it wasn't as big of a deal as it is today, and following it up with an even bigger investment (media estimates at around $10 billion) following the public launch and success of ChatGPT. Microsoft was quick to swoop in on the success, integrating generative AI capabilities across a suite of its products and leaving Google far, far behind. It's important to note, however, that Google has been in the AI game for much longer, though not necessarily in the ways people might think. Google is making available its intelligence-powered tools to enterprise customers at a monthly price of $30 per user, the same as rival Microsoft's "Copilot" AI-powered office software suite, Reuters reported. Furthermore, the Alphabet-owned company also announced a new version of its custom-built AI chips that is reportedly optimized for genAI and large language models. OpenAI, on the other hand, seems to be playing an entirely different game. The Sam Altman-founded company is looking to offer enterprise customers a version of ChatGPT that keeps their trade secrets safe. Called ChatGPT Enterprise, this version of the popular generative AI model offers enterprise-grade security and privacy that protects large businesses' data as they embark on their own AI journeys. Google ranked #1 on HackerNoon's Tech Company Rankingsthis week. Facebook Down But Not Out 🇨🇦 Meta might low key be one of the most evil corporations in the world, but its antics hasn't stopped people from using its service. ICYMI: Meta banned the sharing of news across its platforms Facebook and Instagram in Canada after the government passed a law requiring the company to pay domestic news providers for sharing their content on its platform. Normally, this would have been fine, but the Canadian government wasn't happy that the company maintained the ban while wildfires were raging across Canada's western province of British Columbia. The government argued the company's "reckless" ban on domestic news had essentially left its people locked out of receiving important data about the fires. But Meta didn't care, arguing instead that users didn't come to its platform for news, which made up less than 3% of the content on its users' feeds anyway, and forcing it to pay for content was just bad for its business. Well, a new report from Reuters just might give credence to the company's claims. According to the report, Canadians' usage of Facebook has remained largely the same as before the news ban. This could potentially complicate matters for the Canadian government, which was hoping to bring Meta around to its point of view. We'll keep you posted on updates as we get them. Facebook ranked #4 on HackerNoon's Tech Company Rankings this week. Instagram was #5, while parent company Meta was on the #75 spot. 👋 You’re reading part 2 of HackerNoon's Tech Company News Brief, a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Part 1 went live yesterday. Prefer reading the whole thing a day early AND in one go? No problemo! Just subscribe here to receive the complete newsletter in your inbox every Tuesday. In Other News.. 📰 Google’s AI-powered note-taking app is the messy beginning of something great — via The Verge.
Intel says new 'Sierra Forest' chip to more than double power efficiency — via Reuters.
OpenAI Passes $1 Billion Revenue Pace as Big Companies Boost AI Spending — via The Information.
Meta avatars are finally getting legs (in beta) — via TechCrunch.
AI tools make things up a lot, and that’s a huge problem — via CNN.
Grayscale's big court win boosts Bitcoin and crypto sentiment — via Axios.
Tesla ordered by auto regulators to provide data on ‘Elon mode’ Autopilot configuration — via CNBC. And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan, Editor, Business Tech @ HackerNoon All rankings are current as of Monday and may change by the time of publication. To view the latest ranking, visit HackerNoon’s Tech Company News Pages. Apparently not satisfied with handing over the power of generative AI to the masses, both Google and OpenAI are now looking to further commercialize their technologies by targeting the big fish. Google Google Just recently, Google and OpenAI announced that they would be offering a version of their generative AI tools tailored for enterprise customers. In Google's case, the company is playing catch up with Microsoft after fumbling its big generative AI reveal via Bard. Microsoft Microsoft fumbling fumbling Microsoft has had a big lead over Google, having initially invested in OpenAI back when it wasn't as big of a deal as it is today, and following it up with an even bigger investment (media estimates at around $10 billion) following the public launch and success of ChatGPT. Microsoft was quick to swoop in on the success, integrating generative AI capabilities across a suite of its products and leaving Google far, far behind. It's important to note, however, that Google has been in the AI game for much longer, though not necessarily in the ways people might think. Google is making available its intelligence-powered tools to enterprise customers at a monthly price of $30 per user, the same as rival Microsoft's "Copilot" AI-powered office software suite, Reuters reported . Furthermore, the Alphabet-owned company also announced a new version of its custom-built AI chips that is reportedly optimized for genAI and large language models. reported reported OpenAI, on the other hand, seems to be playing an entirely different game. The Sam Altman-founded company is looking to offer enterprise customers a version of ChatGPT that keeps their trade secrets safe. Called ChatGPT Enterprise, this version of the popular generative AI model offers enterprise-grade security and privacy that protects large businesses' data as they embark on their own AI journeys. Called Called Google ranked #1 on HackerNoon's Tech Company Rankings this week. Tech Company Rankings Facebook Down But Not Out 🇨🇦 Facebook Down But Not Out Meta might low key be one of the most evil corporations in the world, but its antics hasn't stopped people from using its service. Meta Meta most evil corporations most evil corporations ICYMI: Meta banned the sharing of news across its platforms Facebook and Instagram in Canada after the government passed a law requiring the company to pay domestic news providers for sharing their content on its platform. Normally, this would have been fine, but the Canadian government wasn't happy that the company maintained the ban while wildfires were raging across Canada's western province of British Columbia. Facebook Facebook Instagram Instagram The government argued the company's "reckless" ban on domestic news had essentially left its people locked out of receiving important data about the fires. But Meta didn't care, arguing instead that users didn't come to its platform for news, which made up less than 3% of the content on its users' feeds anyway, and forcing it to pay for content was just bad for its business. less than 3% less than 3% Well, a new report from Reuters just might give credence to the company's claims. According to the report, Canadians' usage of Facebook has remained largely the same as before the news ban. This could potentially complicate matters for the Canadian government, which was hoping to bring Meta around to its point of view. We'll keep you posted on updates as we get them. Facebook ranked #4 on HackerNoon's Tech Company Rankings this week. Instagram was #5, while parent company Meta was on the #75 spot. 👋 You’re reading part 2 of HackerNoon's Tech Company News Brief, a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Part 1 went live yesterday. Prefer reading the whole thing a day early AND in one go? No problemo! Just subscribe here to receive the complete newsletter in your inbox every Tuesday. 👋 You’re reading part 2 of HackerNoon's Tech Company News Brief, a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Part 1 went live yesterday. Prefer reading the whole thing a day early AND in one go? No problemo! Just subscribe here to receive the complete newsletter in your inbox every Tuesday. You’re reading part 2 of HackerNoon's Tech Company News Brief, a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Part 1 went live yesterday. Prefer reading the whole thing a day early AND in one go? No problemo! Just subscribe here to receive the complete newsletter in your inbox every Tuesday. part 2 Part 1 Part 1 here complete In Other News.. 📰 In Other News.. 📰 Google’s AI-powered note-taking app is the messy beginning of something great — via The Verge. Intel says new 'Sierra Forest' chip to more than double power efficiency — via Reuters. OpenAI Passes $1 Billion Revenue Pace as Big Companies Boost AI Spending — via The Information. Meta avatars are finally getting legs (in beta) — via TechCrunch. AI tools make things up a lot, and that’s a huge problem — via CNN. Grayscale's big court win boosts Bitcoin and crypto sentiment — via Axios. Tesla ordered by auto regulators to provide data on ‘Elon mode’ Autopilot configuration — via CNBC. Google’s AI-powered note-taking app is the messy beginning of something great — via The Verge . The Verge The Verge Intel says new 'Sierra Forest' chip to more than double power efficiency — via Reuters . Reuters Reuters OpenAI Passes $1 Billion Revenue Pace as Big Companies Boost AI Spending — via The Information . The Information The Information Meta avatars are finally getting legs (in beta) — via TechCrunch . TechCrunch TechCrunch AI tools make things up a lot, and that’s a huge problem — via CNN . CNN CNN Grayscale's big court win boosts Bitcoin and crypto sentiment — via Axios . Axios Axios Tesla ordered by auto regulators to provide data on ‘Elon mode’ Autopilot configuration — via CNBC . CNBC CNBC And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan, Editor, Business Tech @ HackerNoon All rankings are current as of Monday and may change by the time of publication. To view the latest ranking, visit HackerNoon’s Tech Company News Pages. All rankings are current as of Monday and may change by the time of publication. To view the latest ranking, visit HackerNoon’s Tech Company News Pages . Tech Company News Pages

Google, OpenAI Now Target the Big Boys with Enterprise AI offerings

Google, OpenAI এখন এন্টারপ্রাইজ এআই অফার সহ বড় ছেলেদের লক্ষ্য করুন

Google und OpenAI richten sich jetzt mit Enterprise-KI-Angeboten an die Großen

Google y OpenAI ahora se dirigen a los grandes con ofertas de IA empresarial

Google et OpenAI ciblent désormais les grands avec des offres d'IA d'entreprise

Google, OpenAI अब एंटरप्राइज़ AI पेशकशों के साथ बड़े लड़कों को लक्षित करते हैं

Google と OpenAI、エンタープライズ AI サービスで大手企業をターゲットに

Google, OpenAI, 이제 엔터프라이즈 AI 제품으로 대기업을 목표로 삼습니다.

Google e OpenAI agora visam os grandes com ofertas de IA empresarial

Google ve OpenAI Artık Kurumsal Yapay Zeka Teklifleriyle Büyük Çocukları Hedefliyor

Google, OpenAI hiện nhắm mục tiêu vào các ông lớn với các dịch vụ AI dành cho doanh nghiệp

谷歌和 OpenAI 现在通过企业人工智能产品瞄准大公司

Earlier this month, the United States Bureau of Labor Statistics released its monthly jobs report which revealed that postings are from pre-pandemic levels, and this after the tech sector experienced massive layoffs in 2022 and 2023. software development job down 28% What used to be a cushy career path in development and IT is now changing, and other factors such as advancements in artificial intelligence (AI) are also making it harder for dev professionals to secure jobs and advance their . careers Despite challenges, remain resilient and are taking steps to improve their hireability — and their employers should take note. software developers The software development job crisis Following an explosion of technology job during the pandemic, 165,269 tech employees were laid off in 2022, followed by another 263,180 in 2023, to job market watchdog Layoffs.fyi. And thus far in Q1 of 2024, there have been 50,158 layoffs, on pace to keep up with the last two years’ numbers. hiring according What’s more, as other sectors begin to recover from the economic downturn of the past two years, the tech sector continues to struggle. The bureau’s report revealed that tech job postings are 25% below pre-pandemic levels, with software development harder hit at -28%. In an with CNBC, ZipRecruiter’s Chief Economist Julia Pollak said the numbers “suggest that the ‘tech-session’ is still not behind us despite this huge rally in the stock market.” interview Software and IT professionals are also worried by the existential threat that AI poses to their livelihoods, especially with the wide adoption of generative AI like ChatGPT after its much publicized launch in November of 2022, and the recent of Peter Thiel-backed Cognition Labs, which bills itself as “the first AI software engineer.” launch A January from media company Motherboard and Blind, an anonymous platform for verified employees, found that 90% of software engineers found it more difficult to get a job, with 66% qualifying it as “much harder.” Additionally, 80% said the job market was more competitive, while only 6% were “extremely confident” in their job prospects, and 60% of surveyed engineers said they thought their companies would hire less developers due to AI. survey “Of course the aftermath of the layoffs has created an atmosphere of job insecurity, prompting developers to focus on maintaining their current positions,” said Kirimgeray Kirimli, President of Flatiron Software, a full stack development firm. “Simultaneously, there is a pressing need to strategically advance their careers by acquiring new skills and staying abreast of new technologies.” Software developers increasing their chances of getting hired As pressure mounts, software professionals are looking for ways to keep them successful in a competitive job market. Ironically, some job-seekers are to help them game the resumé selection process. But there are other ways of standing out. turning to AI As in any job space, Kirimli recommends making connections to help open up job opportunities. “Building a network is essential for every professional, not just people working in the field of technology. I have found many of my jobs through personal networks and I have seen a lot of executives move into new roles with the help of their networks,” he said. One of the best ways to build connections is by helping others. Working on a , reaching out to past colleagues or alumni from college to see if you can contribute to projects they’re working on can help. GitHub project Additionally, being active on social media, contributing valuable advice to conversations surrounding software development issues can also get you noticed by companies looking for workers. What’s more, staying active as a developer, even when you’re out of work, can make you attractive to recruiters. John Macdonald, a long-time software development team leader, he asks developers one simple question when hiring: What are you coding at the moment? said This type of question can separate those with a true passion for software development, from the rest. Although at times it may feel discouraging, out of work developers should keep coding on passion projects that interest them, or upskilling themselves through further education. “As a software engineer specifically, you will always have to learn and improve yourself,” said Kirimli. “Emerging advancements in AI will change the software development space, but as long as engineers stay up to date, there will be work to be done … Whether this will be in the form of prompt engineering or something else, time will tell.” How can managers best set up developers for success? We mustn’t lay the full responsibility of landing a job on the developers. The tech industry, and society as a whole, must have a long discussion about the ramifications of companies using AI to replace human talent. Labor unions are to get tech workers a seat at the bargaining table with companies that are implementing AI, and last December, Microsoft to union contract language governing its use of AI, although it applied to a small gaming studio within the company. working agreed On a more personal scale, managers who are interested in the success of their employees can also do more to set them up for career advancement. Kirimli, the former software engineer, said that fostering an environment that values continued learning is “crucial” for employees’ wellbeing. “This involves supporting educational initiatives, providing resources for skill development, and ensuring that our teams stay ahead in the ever-evolving tech landscape,” he said. According to Sashank Purighalla, CEO of cloud management platform BOS Framework, “Companies should create a ‘safe space’ for experimentation within project boundaries when possible. This allows developers to test new tools, explore innovative approaches, and learn from experiences—including failures—in a controlled environment, fostering creativity and problem-solving skills. Additionally, evolving the paradigm of how promotions and demotions dealt with in the tech space is also key. “We recognize the significance of data-driven decision-making” in the promotion process, said Kirimli. Rather than relying on the sentiment of the manager, developers are encouraged to showcase their contributions through quantifiable results and measurable impact. Kirimli said his company uses a proprietary tool, called Snapshot Reviews, to allow for a clear picture of a developer’s performance, their contributions, and how they compare to the rest of their team. The software uses AI to analyze Jira tickets and GitHub commits to provide feedback and render performance graphics for teams. Additionally, hiring managers should ensure they’re setting new hires up for success. “The problem isn’t really the quantity of positions, it’s the number of quality positions with clear expectations and skill matching,” said Sajid Mohamedy, an Executive Vice President at technology consultancy Nisum. “A data science degree doesn’t make you a great software engineer. Some of the best engineers I’ve come across don’t have degrees at all. The challenge is to evaluate an engineer correctly—and this process can be quite demanding for both parties.” He added, “I’m convinced that coding requires a special mindset, somewhat akin to math/logic. The better strategy is to find candidates with the right mentality and invest in new hire training periods to transfer their skills to the business use case.” The so-called “tech-session” looks to be on track to continue into 2024, and with the uncertainty surrounding AI, unfortunately, the job market for developers will most likely remain competitive throughout the year. But developers can, and should, do what is necessary to keep advancing their careers and making themselves more hireable — and we should help them too! This article was originally published by on Stiven Cartagena The Tech Panda.

The Competitive Landscape of the Software Development Job Market

Artificial intelligence (A.I.) has rapidly emerged as a driving force in our increasingly digital world, transforming industries and reshaping how we live and work. From advanced data analytics to intelligent automation, A.I. technologies have become pivotal in driving innovation and unlocking new possibilities across diverse sectors. As we stand at the precipice of an future, it is crucial to recognize the individuals leading the charge and pushing the boundaries of what is possible. AI-driven This article introduces 15 international A.I. executives at the forefront of this . Each executive has been selected based on their roles and the company technologies they represent, showcasing the vast array of A.I. applications reshaping their respective industries. technological revolution Join us on this exploration of these executives as we highlight their visionary approaches, technological innovations, and profound impact on the A.I. landscape. , EVP of Growth & Delivery at Nisum Sajid Mohamedy Sajid is a seasoned strategy professional and accomplished entrepreneur known for creating and expanding enterprises successfully. He possesses expertise in business planning, entrepreneurship, marketing analytics, international growth, mergers and acquisitions, venture capital, and market analysis. With a solid educational background and relevant experience, Sajid excels in navigating the dynamic business landscape and consistently demonstrates exceptional business acumen. Nisum, a technology consulting partner, specializes in designing and building custom digital commerce platforms for enterprises of all sizes. They leverage an AI-driven forecasting framework, resulting in a 25% increase in forecast accuracy. , Sr.Manager at ServiceNow Bharathi Ramadass Bharathi Ramadass, a certified ServiceNow Administrator, has expertise in Agile Scrum methodology and extensive experience building custom applications and implementing I.T. and H.R. modules in ServiceNow. With proficiency in workflows, scripting, and enhancements, Bharathi successfully integrated IBM Watson Assistant into ServiceNow. This AI-driven conversational agent empowers employees to deliver reliable customer responses, transfer conversations to live agents, and proactively address user issues. Bharathi’s dedication to digital transformation has contributed to ServiceNow’s remarkable growth, expanding from two to over 300 use cases, with a significant monthly engagement of 20% of employees with the assistant. , Head Product Manager at Transmetrics Hristo Hadjitchonev Hristo Hadjitchonev, an experienced professional in the software development industry, boasts an impressive track record spanning over three decades. He has a rich academic background, pursuing studies in Analytical Modeling in Business Intelligence and Data Mining solutions. As the Head Product Manager for Transmetrics, Hristo spearheads an ambitious endeavor to create a cutting-edge Data Science and Forecasting framework that will shape the industry’s future. Transmetrics optimizes logistics planning and asset management by leveraging the power of predictive analytics and artificial intelligence. , PhD, Co-Founder and CEO at Affectiva Rana el Kaliouby Rana el Kaliouby, an Egyptian-American scientist, entrepreneur, and angel investor, is dedicated to humanizing technology in our digital world. As the Co-Founder of Affectiva, an AI company focused on emotional intelligence, she has brought Emotion AI to over 90 countries and various industries, including automotive and media analytics. Rana’s bestselling memoir, “Girl Decoded,” chronicles her personal journey and her mission to bridge emotional intelligence and technology. Passionate about ethics and inclusion in AI, she actively participates in industry organizations and advocates for diversity. Rana believes in the transformative power of human connection. , Founder & CTO at IndustrialML Arjun Chandar Arjun Chandar is a highly accomplished professional with an impressive academic background. He holds a Bachelor of Science in Mechanical Engineering from Caltech and a Master’s in Manufacturing from the Massachusetts Institute of Technology (MIT). Arjun excels as an entrepreneur, business leader, data scientist, engineer, and inventor, specializing in Industry 4.0. IndustrialML is a renowned enterprise software company that specializes in serving industrial customers. Their expertise lies in developing essential tools to ensure seamless operations on production lines. The IndustrialML platform connects data from various sources, providing valuable context about the production status. By integrating real-time monitoring, machine vision, and advanced analytics applications, they deliver actionable insights to operators and engineers. , Head of Strategy & Business Transformation at Curren Katz Johnson & Johnson Curren Katz is a seasoned analytics leader with a track record of success in the healthcare industry. With over 10 years of leadership experience in the U.S. and Europe, Curren has spearheaded the development of numerous analytics and data science products for payers, providers, and pharmaceutical companies. They possess Data Science, Digital Health, Statistics, and Operations Research expertise. Curren’s background in cognitive neuroscience and machine learning allows them to apply artificial intelligence techniques to complex, unstructured data. Currently, Curren is driving innovation in clinical trials, focusing on decentralized trials, artificial intelligence, real-world data, and precision medicine. , Founder, and CEO at NexusLeap Madhav Srinath Madhav is a distinguished professional with a strong background in Artificial Intelligence. His educational accomplishments include graduating Magna Cum Laude from Georgia Tech with a bachelor’s degree in Industrial Engineering. He further expanded his knowledge by earning a master’s degree in Computer Science from his alma mater. Madhav’s dedication to continuous learning is evident through his active AWS certifications, including associate and speciality levels. NexusLeap is an analytics consulting company specializing in customized cloud solutions, equipping companies with scalable decision-making tools, known by its customers as a “friendly neighborhood analytics provider”. , Founder & CEO at TheDeltacube.ai Ujjyaini Mitra Ujjyaini Mitra is a strategic advisor at Zupervise and the founder & CEO of TheDeltacube.ai, where her focus goes beyond merely being “Best in Class.” She is deeply passionate about building “Next in Class” innovative AI-driven solutions using design thinking and cutting-edge technology. With over 14 years of leadership experience, Ujjyaini has successfully fostered a data-centric culture in major organizations across industries like digital media & entertainment, e-commerce, and telecommunications. Her expertise lies in developing data strategies, driving business growth, collaborating with stakeholders, and building cohesive and empowered data science teams. In her free time, Ujjyaini finds solace in practicing Vipassana Meditation, Sivananda Yoga, and exploring the realms of AI and its transformative potential. , Founder and CEO at dotData Ryohei Fujimaki During his tenure, Ryohei, the youngest research fellow in NEC Corporation’s history, played a crucial role in delivering meaningful analytical solutions. Building on his expertise and fresh perspective, he founded dotData to revolutionize automated data science. dotData brings unprecedented speed, scalability, and value to various industries, including Fortune Global 250 clients. dotData is a pioneering company specializing in end-to-end data science automation for enterprises. With unique AI-powered Feature Engineering, dotData eliminates time-consuming tasks, empowering data scientists for higher-value work while enabling data engineers and business analysts to drive data science projects. , CEO & Co-Founder at Agrolly Manoela Morais Manoela N. is a seasoned Enterprise Risk Management professional specializing in Supply Chain Risk Management and Contract Manufacturing Management & Audit. Holding a Chemical Engineering degree from the Federal University of Bahia (Brazil), an MBA in Automation & Process Control, and an M.S. in Financial Risk from PACE University in NYC, Manoela combines technical knowledge with financial acumen. In 2020, Manoela and her team developed Agrolly, a solution for farmers in developing countries, leveraging IBM Watson Studio. Agrolly utilizes A.I. technology to provide tailored information and risk assessments to help farmers optimize crop production and mitigate the impact of extreme weather conditions. The platform also facilitates financial assistance through partnerships with local financial institutions. , Director of Engineering, AI/ML at Semantix AI Lucas Bonatto Lucas is a highly skilled software engineer, holding a Master’s degree in Computer Science from PUC University. With a deep passion for machine learning, he has contributed his expertise to renowned tech companies like OLX and Hewlett-Packard. Additionally, Lucas is the visionary behind Marvin AI, an innovative open-source Artificial Intelligence platform and Elemeno, a comprehensive solution with fully-managed and highly scalable infrastructure. Semantix AI is a prominent leader in Big Data, Analytics, and Artificial Intelligence solutions. They offer innovative and disruptive services, including one-stop-shop Big Data platforms for quickly implementing complex data environments. Their expertise extends to multi-cloud infrastructure, advanced business performance, and industry data governance solutions. , Founder and CEO of Insitro Daphne Koller Koller’s career exemplifies the harmonious synergy between academia and industry within the realm of artificial intelligence. As a long-standing Stanford professor, her focus on machine learning has been influential. In 2012, Koller co-founded Coursera, an ed tech startup, alongside fellow Stanford professor Andrew Ng, now valued at $2.6 billion. Currently, as the CEO of Insitro, Koller’s latest venture applies machine learning to revolutionize pharmaceutical research. Backed by significant investments, including $250 million from Andreessen Horowitz, Insitro recently forged a major partnership with Bristol Myers Squibb. Koller’s aim is to overcome challenges in biomedical applications of machine learning, paving the way for novel, affordable therapies, and building a diverse and exceptional team. , CEO at QuickBlox Nate Macleitch Nate MacLeitch brings over 20 years of diverse industry experience spanning telecom, media, software, and technology. He has excelled in leadership roles, including Head of Sales at WIN Plc (Cisco), Twistbox Entertainment’s COO, and QuickBlox’s CEO. Beyond his impressive career, Nate is an accomplished advisor and investor, supporting startups like Springboard Mobile and TechStars. He holds degrees from the University of California, Davis, and The London School of Economics and Political Science. As CEO of QuickBlox, Nate pioneered chat API solutions to meet the growing demand for seamless remote real-time communication. QuickBlox remains committed to providing user-friendly, affordable, secure, and feature-rich communication solutions that elevate the user experience. , CEO at videoBIO Recruiter Catharine Fennell Catharine Fennell is the visionary Founder and CEO of videoBIORecruiter, a cutting-edge digital A.I. video platform revolutionizing the recruitment, interviewing, training, and talent matching processes. Through videoBIO’s software, hiring teams can streamline and modernize their talent evaluation processes while maintaining a human touch. Utilizing custom-trained machine algorithms and automated competency scoring powered by IBM Watson Studio, videoBIO Recruiter provides enterprises and universities with comprehensive, on-demand video application, screening, and interviewing solutions. Catharine’s leadership and commitment to A.I. innovations have garnered industry recognition, multiple awards, and remarkable business growth for videoBIO. , Manager, ITSM & Technical Buyer at Rasha Ragab Saleh Telecom Egypt Rasha Ragab, an accomplished Information Technology Service Management Manager with a rich background in the telecommunication industry, has played a crucial role in transforming Telecom Egypt’s customer experience. By spearheading the integration of an A.I. Chatbot and leveraging the power of IBM Watson Assistant, Rasha has enabled the company to provide exceptional customer service with efficient problem resolution and request fulfillment. The AI-powered digital assistant has successfully served over 500,000 active monthly users through Telecom Egypt’s website, and future integrations with platforms like Facebook and WhatsApp are planned to elevate the service experience further, boost customer satisfaction, and reduce churn rates. This article was originally published by on Alexander Garcia The Sociable.

15 Global AI Executives Revolutionizing Diverse Industries

In the two brief months since its launch, has already become the fastest growing app in history. Being used to deliver everything from and essays through to a variety of sophisticated search interfaces, it’s been hailed as an industry disruptor that will make endless professions obsolete and even threaten to . ChatGPT news articles, quizzes rattle the likes of Google Pretty impressive stuff for what is, essentially, a chatbot. ChatGPT and other new generative AI tools clearly represent a noteworthy evolution in the sophistication of AI as a technology and the capabilities that “off-the-shelf” solutions can offer. However, as with any trend that comes with so much fanfare it’s important to sort the facts from the hype. Results so far are certainly far from perfect, given the number of , suggesting that AI likely isn’t ready for world domination just yet. highly publicized errors Still, the global AI market is projected to reach and the  transformative technology was on every top executives’ lips at this year’s for good reason. The launch of ChatGPT has been a seminal moment and served at the very least to capture our collective imagination at where this technology may lead next. USD $1394.30 billion by 2029 World Economic Forum in Davos We already know that AI has near endless use-cases which will continue to morph alongside the sophistication of the technology, but what about the big picture? Here are three predictions on what hype surrounding ChatGPT signals for the future. More specialized university courses and graduates will emerge Next, the launch of ChatGPT has shown us how many questions still exist when it comes to the implementation of advanced AI technology. We’ll see a spike in AI-related university courses, but these won’t be limited to the computer science department. The future of AI will touch on everything from economic theory and business management to public policy and law, meaning future graduates need to be better equipped with specialized courses that equip them with comprehensive theory that can manage the future of this technology. In good news, the wheels for this change are already in motion: Stephen A. Schwarzman donated $5 million to to help shape the future of AI in a way that benefits the public interest and a staggering $188 million to to support research into the ethics of AI. Harvard Business School Oxford University Such sizable donations like these highlight the importance of AI-related courses across all fields of study to help us develop regulation laws, competitive advantage regulations and everything in between as this transformative technology continues to take hold. AI will become commonplace in the arts Cultural mediums have always been used to dive into the potential impact that technologies will have on society, and AI has been a recurring character for years. For example, the movie Her explores a lonely writer who falls in love with an operating system scarily adept at adjusting to create the perfect partner for the protagonist. Likewise, in Black Mirror’s episode “ ,” a widow receives a clone of her deceased husband that uses chat-bot-like technology to build an AI model based on his online data record. These references are from the last decade but ring ever more eerily true given the launch of ChatGPT. Be Right Back But beyond seeing more instances of movies predicting where advanced computing may lead society in the decades to come, it’s highly likely that we’re going to see a continued increase in AI being used as a production tool across the arts. Image generating AI has already been producing some weird and wonderful results when incorporated into art projects, like . these spine-tingling recreations of the Met Gala https://twitter.com/rob_sheridan/status/1521264331895107584?s=20&embedable=true Following ChatGPT we’re likely to see a revamped interest in exploring where this technology could take us and an increased integration of the technology into the creative process itself for some results. weird and wonderful That said, generative AI has come under serious scrutiny from the arts community in recent months, as felt by the recent of the Colorado State Fair and general discourse on how closely any AI-generated art strays into the territory of as the technology must have some kind of source material to work with. digital arts winner plagiarism by default Yet once any form of progress reaches a certain level of momentum and usability it can only be contained for so long. The fear mongering around AI-generated art is likely due to it being so new but it’s as much a tool in art as it is in business. Chat-GPT can’t run a company in much the same way that Dall-ee 2 couldn’t graduate with a degree in the arts unaided. In the future, generative AI will become as familiar as Photoshop or Illustrator as a to take care of repetitive tasks like editing and elevate the production process into exciting new territory with their expert creative guidance. tool that’s used by artists A new breed of AI business consultant will emerge The rush is on among tech companies large and small to add the latest hot AI technology into their products and services. Yet given the tech’s impressive capabilities and noteworthy shortcomings, AI consultants will become increasingly necessary. For example, a business could hope to use ChatGPT to support its online customer service chat. But, as Bing found during the beta launch of its ChatGPT-driven search interface, the software hasn’t been consistent, building and arguing with users to name a couple of examples. curious shadow personalities Companies need to be sure that any AI solution being used to support real business processes can be trusted. In future, working specialized AI consultants who are well-versed in both the technology and considerations for practical implementation will offer significant business value and become as commonplace as seeking expert legal or financial advice. We’re already seeing a rise in the large multinationals seeking expertise to help smooth the integration of new AI use cases, such as . Coco-Cola’s collaboration with Bain for AI consultancy In tandem, we’ll see a rise in AI-specialized business consultancies to meet this demand across sectors. Nisum, an international technology developer has recently announced a new partnership with ​Databricks to drive business transformation leveraging AI technology and data-oriented analytics to prepare for this future and ITRex helps Fortune 500 companies and startups , apart from automating operations, boosting customer experiences, and supporting smart decision-making. launch breakthrough AI products The AI progress challenges we can’t ignore In Stephen Hawking’s posthumously published book, he notes that Brief Answers to the Big Questions, “the short-term impact of AI depends on who controls it, the long-term impact depends on whether it can be controlled at all.” For this reason, there are a number of areas we need to monitor as this technology develops: It’s been well-documented that AI products are prone to bias due to the developers who built the software or the data sets that they’re training from. If we don’t address this reality, the problem will only compound as the technology scales. To make AI as valuable as possible for society, diversity will need to be improved from the earliest stages of development through to the rules and regulations surrounding its use in the private and public sectors. Next, the legal and protective implications with regards to AI are likely to be much trickier to unpack. On the one hand, the technology is so transformative that our current policies and frameworks when it comes to fair practice, competitive advantage, data control and IP ownership are the more widespread AI becomes in everyday usage. Here, the aforementioned focus on bringing AI ethics and law into prominence at our educational institutions will be crucial to manage this going forward. unlikely to suffice Finally, there are still a number of technical question marks on how AI performs and delivers its results. For example, the so-called “ ” in which inputs and processes are hidden from public view, and “black box” results in which even the developers can’t explain how the software managed to reach a conclusion are both great examples of this in action. If we hope to give AI more responsibility in future the presence of unexplainable decisions in algorithms must be solved. black box algorithm With over 100 million users and counting, ChatGPT has already become one of the most seminal product launches we’ve seen in recent decades. While the jury is still out on just how disruptive generative-AI will be in the near-term, it has shown us that we’re just scratching the surface when it comes to where, and how, we use AI in the future. This article was originally published by Katie Konyn on 150sec.

ChatGPT Has Proven that AI Mass Adoption is Inevitable

ChatGPT প্রমাণ করেছে যে AI ভর গ্রহণ অনিবার্য

ChatGPT hat bewiesen, dass die Masseneinführung von KI unvermeidlich ist

ChatGPT ha demostrado que la adopción masiva de IA es inevitable

ChatGPT a prouvé que l'adoption massive de l'IA est inévitable

चैटजीपीटी ने साबित कर दिया है कि एआई मास एडॉप्शन अनिवार्य है

ChatGPT は、AI の大量採用が避けられないことを証明しました

ChatGPT는 AI 대량 채택이 불가피하다는 것을 입증했습니다.

O ChatGPT provou que a adoção em massa da IA é inevitável

ChatGPT, Yapay Zekanın Kitlesel Benimsenmesinin Kaçınılmaz Olduğunu Kanıtladı

ChatGPT đã chứng minh rằng việc áp dụng hàng loạt AI là không thể tránh khỏi

ChatGPT 已经证明人工智能的大规模采用是不可避免的

Intelligent DevOps: 8 Lessons Learned from Nature

ইন্টেলিজেন্ট ডিওঅপস: প্রকৃতি থেকে শেখা ৮টি পাঠ

Intelligentes DevOps: 8 Lektionen aus der Natur

DevOps inteligente: 8 lecciones aprendidas de la naturaleza

DevOps intelligent : 8 leçons tirées de la nature

इंटेलिजेंट DevOps: प्रकृति से सीखे गए 8 सबक

インテリジェントな DevOps: 自然から学んだ 8 つの教訓

지능형 DevOps: 자연에서 배운 8가지 교훈

DevOps Inteligente: 8 Lições Aprendidas com a Natureza

Интеллектуальный DevOps: 8 уроков, извлеченных из природы

Akıllı DevOps: Doğadan Öğrenilen 8 Ders

DevOps thông minh: 8 bài học rút ra từ thiên nhiên

智能 DevOps：从大自然中汲取的 8 个教训

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