The US Department of Energy announced that Ford would get $9.2 billion as part of a conditional loan to help with the development of three enormous plants to produce batteries for electric vehicles. Since the bailouts following the 2009 Great Recession, the enormous loan is the largest government grant given to an automaker.
The loan comes from the Advanced Technology Vehicles Manufacturing (AVTM) programme of the DOE, which is well known for helping to establish Tesla and more recently giving a boost to a partnership between General Motors and LG Energy Solution to help fund the development of a new lithium-ion battery manufacturing facility.
The loans are a part of a larger initiative by the Biden administration to increase EV production as it tries to catch up with China, which now dominates around three-quarters of the world’s battery production. It’s also a key component of the White House’s strategy to support sustainable energy in the face of the worsening climate problem.
Ford has stated that it will invest $11.4 billion in three battery plants, two in Kentucky and one in Tennessee, along with South Korean battery producer SK Innovation. The two businesses intend to develop enough capacity through a joint venture named BlueOvalSK to supply 129 GWH of capacity annually, which would be sufficient to power 2 million EVs yearly by 2026.
Ford stated that it appreciated the financing. According to Ford’s treasurer Dave Webb, it’s going to help make great EVs available to more customers while powering thousands of well-paying jobs and American manufacturing. “Collaboration between the public and private sectors has historically expedited significant technological transitions. The DOE’s insight in this area will assist in facilitating the switch to zero-emissions transportation,” he said
Networking is a skill and is crucial in every profession.
As the field of data science continues to grow and evolve, networking has become increasingly important for professionals looking to advance their careers. Networking enables people to connect with other professionals, keep abreast of emerging trends and technology, and access employment openings that would not otherwise be made public.
This blog will offer advice and techniques for networking within the data science community to assist you in advancing your career and finding job possibilities. These pointers help establish connections and foster meaningful interactions within the data science community, regardless of whether you are a data scientist, data analyst, data engineer, or any other type of data professional. Let’s look at how you might use networking to get employment in the fascinating subject of data science.
Join Data Science Communities
Joining data science groups is one of the best methods to network. People who share a common interest in data science and are keen to network with others in the industry make up the data science community. By joining these communities, you can expand your network, learn new skills, get expert feedback, Collaborative opportunities, and access job opportunities.
You may join several local and online data science communities. Stack Overflow, GitHub, and Kaggle are a few well-known online communities. You may network with other data professionals through these forums, work together on projects, and show prospective employers your skill set. Offline networks like Meetup groups, data science conferences, and regional data science organizations offer chances to interact in person, attend workshops and speeches, and connect with regional data science experts.
Therefore, it is essential to engage in a data science community actively. This entails interacting with neighbors, imparting knowledge, gaining skills, and participating in initiatives and debates. You may position yourself as a thought leader in the community and develop connections with other data professionals by actively engaging. You may remain current on the newest industry trends and innovations by participating in these communities.
Attend Data Science Events
Another efficient strategy to network in the data science community and discover employment prospects is to attend data science events. These gatherings allow networking with other data experts, where you can find innovative tools and methods and meet prospective employers.
You may attend various data science events, such as conferences, meetings, and seminars. The yearly Data Science Summit and regional data science meetups are prominent data science events. These events cover trending topics, best practices, etc. These events are fun and provide you with a lot of value.
Preparing to get the most from data science events is essential. This entails doing your homework in advance, selecting the speakers and themes that appeal to you, and preparing inquiries to pose during question-and-answer sessions or networking breaks. Additionally, you can prepare your elevator pitch to describe your qualifications to potential employers or business partners.
Furthermore, being involved and present throughout the event is crucial. This includes paying attention during presentations, participating in Q&A sessions, and making small talk with other participants. You may establish yourself as an active member of the data science community and create connections with other experts by being involved and present.
Utilize Social Media
And it will be really easy for you. LinkedIn, Twitter, and Reddit are a few of the well-known professional social media platforms for networking in data science. Because it enables you to connect with other data professionals, discuss your skills and expertise, and highlight your work through a personal profile, LinkedIn is beneficial for professional networking. Conversely, Twitter and Reddit allow users to interact with people in the industry, participate in conversations and debates, and keep up with the most recent data science ideas and technology.
You need to have a strategy for using social media while networking. This includes having a specific objective in mind, figuring out who the major players in your sector are, following the major players like Mu Sigma, Quantiphi, Tiger Analytics, etc., and actively interacting with them. For instance, join data science groups on LinkedIn, participate in Reddit debates about data science, or follow and interact with thought leaders on Twitter’s data science community.
Being aware of your brand and internet presence is also crucial. You should do this by ensuring that your social media profiles are current, appropriate, and consistent across all platforms. Also, posting your ideas and achievements can make you stand out and help you to get more opportunities.
Collaborate with Professionals
Working with other data science experts is a beneficial approach to network and discover employment openings in the industry. By collaborating with others, you may benefit from their knowledge and experience, pick up new skills and technology, and meet prospective employers and clients.
One way to collaborate with other professionals in data science is through joint projects or research. This can involve partnering with other data scientists, analysts, or engineers to work on a specific project or research question. By working together, you can combine your skills and expertise to produce high-quality work that is more comprehensive and impactful than what you could achieve alone.
Participating in challenges or contests related to data science is another method of cooperation. These contests allow you to collaborate with other professionals to find solutions to practical issues, display your knowledge and abilities, and network with possible employers and customers.
Collaboration in data science has several advantages. By collaborating with others, you may increase your knowledge and skill sets, create a network of connections in the business, and become aware of future employment openings. Additionally, by combining the skills and viewpoints of other specialists, teamwork might result in more creative and significant solutions.
Conclusion
Networking is a crucial aspect of finding job opportunities in data science. By actively participating in data science communities, staying updated with data science news portals, attending events, utilizing social media, and collaborating with other professionals, build a network of contacts, and gain exposure to potential employers and clients. Moreover, you will learn many things that a course and degree may not teach you.
This is also true; when you start a networking journey, you might feel lost and overwhelmed, but once you are consistent, then your network becomes your net worth.
To recap, some of the tips for networking in the data science community include:
● Joining data science communities
● Attending data science events
● Utilizing social media
● Collaborating with other professionals
We advise our readers to actively engage in data science groups and utilize the advice provided to locate employment possibilities. By implementing these tactics, you may expand your network of connections, demonstrate your knowledge and abilities, and raise your chances of obtaining your ideal position in data analytics. Don’t hesitate to put yourself out there and investigate new possibilities for cooperation and development in the data science community. Keep in mind that networking is a continual activity.
Prime Minister Narendra Modi talked about the enormous potential of artificial intelligence (AI) in the areas of education, training, and learning during his remarks at the G20 education ministers’ meeting. He emphasized the transformative potential of technology and its role in influencing the future of education.
Modi spoke on the crucial role that education plays in the advancement of humankind and civilizations. He described the ministers of education as “Sherpas” guiding humanity towards growth, peace, and wealth.
Prime Minister Modi discussed India’s all-encompassing approach to education, emphasizing the value of fundamental literacy as the cornerstone of youth growth. He praised the government’s “Nipun Bharat” initiative, which aims to increase reading comprehension and numeracy skills. He expressed his happiness that the G20 also acknowledged the significance of fundamental literacy and numeracy.
In order to deliver high-quality education and efficient governance, the prime minister stressed on the necessity for creative e-learning techniques. He covered the “Swayam” online platform’s accomplishments, which provides classes from Class 9 to postgraduate levels.
PM Modi emphasized the significance of reskilling, upskilling, and skilling the youth constantly to ensure their future readiness. He noted India’s project for skill mapping, in which the labor, education, and skill ministries work together to match competences with changing work profiles and practices. To identify and bridge skill gaps, the prime minister urged G20 nations to collaborat.
PM Modi explained the importance of digital technology in fostering inclusivity and recognised its potential as an equalizer and a driver of greater educational access. He also talked about the enormous potential of AI in the fields of education, skill development, and learning. The G20 was urged by the prime minister to find the correct balance between technological opportunities and problems.
AWS generative AI center will receive $100 million from Amazon’s cloud division, the company announced on Thursday. The generative AI technology has gained popularity in the recent months since OpenAI made its ChatGPT chatbot available to the public.
For a tech giant with $64 billion in cash and half a trillion dollars in operational costs annually, it’s a modest investment. However, the investment demonstrates that Amazon Web Services, along with competitors Microsoft and Google, understands the relevance of the current state of generative AI and the necessity of participating in the discussion.
In its most recent statement, Amazon stated that it would be hiring some data scientists, engineers, and solutions architects. The center already collaborates with Highspot, Twilio, RyanAir, and Lonely Planet, according to AWS. It’s a “programme” rather than a physical center, the company informed.
The cloud infrastructure market is dominated by Amazon, which entered the business of renting out servers and data storage to businesses and other organizations before Microsoft and Google. Even though Amazon has used AI extensively for years to operate its Alexa voice assistant and display shopping recommendations, other competitors have made bigger forays into generative AI.
The opening of the AWS Generative AI Innovation Centre was announced amidst ongoing concerns about the company’s capacity to keep up with cloud rivals Microsoft and Google in the race to take advantage of advancements in large language models and new applications of artificial intelligence.
The IT services provider Infosys announced on Thursday that its Infosys Springboard Virtual Learning Platform will now offer a free Artificial Intelligence (AI) certification training.
Infosys AI-first specialists and data strategists, who are the sole in-charge of delivering Infosys Topaz’s AI-first suite of solutions, services, and platforms, will assist in creating the curriculum in order to provide students with skill-sets for the future.
Through the Infosys Springboard Virtual Learning Platform, Infosys will offer certification in AI and generative AI skills, which are essential for obtaining jobs, the company said.
A couple of the courses included in the certification include an introduction to AI and generative AI with a focus on deep learning and natural language processing, as well as a masterclass on the effect of generative AI.
Additionally, an individualized course on “Citizens Data Science” will cover a variety of topics in the field of data science, such as Python programming, linear algebra, probability and statistics, and exploratory data analysis. A certificate will be given to students when they successfully complete the course.
This certification, combined with formal education, is supposed to speed up digital reskilling for participating learners, who can include adults and professionals as well as high school and college students.
Infosys Springboard is a curriculum-rich virtual platform that provides corporate-grade learning experiences on any device with closer educator-learner collaboration for children from Class 6 to lifetime learners.
Google is going public with its own complaint of Microsoft’s anti-competitive actions after years of defending itself against accusations of monopolistic behavior in the U.S. and Europe. Google said that Microsoft exploits unfair licensing terms to “lock in clients” in order to control the cloud computing business, in a letter sent to the Federal Trade Commission on Wednesday.
The letter was written in response to an extensive FTC call for comments on possible anti-competitive behavior in the cloud market. The FTC spokesperson declined to make any additional comments.
Google singled out Microsoft in the complaint, contending that the corporation can make it challenging for its sizable clientele to use anything other than its Azure cloud infrastructure service because of its dominance in the Windows Server and Microsoft Offices markets. Google referred to Microsoft’s licensing requirements as a “complex web” that restricts companies from varying the vendors of their enterprise software.
A serious risk to national security and cybersecurity, according to Google, is posed by such control. It drew attention to a series of hacks that involved Microsoft technologies, notably the SolarWinds hack. Both Microsoft and Google have active cybersecurity practises that address and investigate online threats.
Google has frequently faced antitrust issues. The US Department of Justice filed its second antitrust action against Google in a little more than two years in January, this time focusing on its advertising division.
In a previous action brought by the department in October 2020 under the Trump administration, Google was charged with abusing its dominant status to stifle competition in internet search through exclusionary contracts. Trial in that case is anticipated to begin in September. Large groups of state solicitors have also filed three other antitrust claims against Google, one of which is targeted at the company’s advertising division and is being led by Texas Attorney General Ken Paxton.
Latent Diffusion Model for 3D (LDM3D) is a unique diffusion model that employs generative AI to produce realistic 3D visual content. It was developed by Intel Labs in partnership with Blockade Labs. The diffusion technique is used by LDM3D, the first model in the market, to develop a depth map that results in vibrant, immersive 3D images with 360-degree vistas.
With the help of this research, users will be able to interact with their text prompts in previously unimaginable ways, revolutionizing the way we interact with digital content. Users can convert a literary description of a calm tropical beach, a contemporary skyscraper, or a sci-fi cosmos into a 360-degree detailed panorama using the photos and depth maps produced by LDM3D.
A subset of 10,000 samples from the LAION-400M database, which comprises more than 400 million image-caption pairs, served as the basis for the dataset used to train LDM3D. The researchers annotated the training corpus using the Dense Prediction Transformer (DPT) large-depth estimation model, which was previously created at Intel Labs.
For every pixel in a picture, the DPT-large model delivers incredibly accurate relative depth. The LAION-400M dataset was created for research purposes to allow for model training on a bigger scale for the benefit of various research communities. An Intel AI supercomputer with Intel Xeon processors and Intel Habana Gaudi AI accelerators is used to train the LDM3D model. To create 360-degree views for immersive experiences, the final model and pipeline integrate the generated RGB image and depth map.
Intel and Blockade researchers created DepthFusion, a programme that uses common 2D RGB photographs and depth maps to produce realistic and interactive 360-degree view experiences, to show the potential of LDM3D. Text prompts are transformed into engaging digital experiences by DepthFusion using TouchDesigner, a node-based visual programming language for real-time interactive multimedia content.
Dropbox has announced Dropbox Ventures, a new $50 million venture effort, to promote the revolutionary potential of artificial intelligence in defining the future of work. This project is concentrated on funding the next generation businesses that are using AI in cutting-edge ways to transform business operations.
Dropbox Ventures’ portfolio businesses will benefit from mentorship opportunities in addition to financial resources, enabling them to create and offer novel experiences to Dropbox’s large user base of more than 700 million registered customers.
Dropbox VP and GM Sateesh Srinivasan said, “We at Dropbox have a unique perspective on what it takes to assist these kinds of businesses in moving to the next level of growth and having an effect because we started as an early-stage startup with a straightforward idea that expanded to a service used by hundreds of millions of people worldwide.”
Since a few years ago, VCs have progressively boosted their investments in AI, recently encouraged by the rise of generative AI. For instance, the venture capital arm of Salesforce, Salesforce Ventures, intends to invest $500 million in firms creating generative AI solutions. A $175 million fund has also been formed by OpenAI, the company behind the popular chatbot ChatGPT, to invest in AI startups.
“We’ve been investing in AI and machine learning for a long time, and we started incorporating machine learning across our products as far back as 2016 to make work more efficient for our customers’ and help them save time. Recent developments in AI and machine learning have opened up a whole new universe of possibilities in the last several months, and we believe that this will help us advance in our mission to create a more enlightened way of working,” Srinivasan added.
In 2025, devotees who come to the city for the Mahakumbh will be closely monitored by Indian Railways, in partnership with the Smart City Project, using “AI-based” cameras placed at strategic locations across the city.
This was decided at a meeting on Monday night to talk about the Mahakumbh 2025 preparations, which was presided over by the Divisional Railway Manager (DRM) for Prayagraj division.
Chandra Mohan Garg, the Chief Executive Officer (CEO) of the Smart City Project and Municipal Commissioner, was present at the meeting. Together with their respective expert teams, the two authorities talked about cooperating during the Mahakumbh in 2025.
Administrations in the civil and railway sectors are getting ready to communicate information more promptly. In order to notify devotees of crucial information, live train feeds, the Mela area, and other city areas, it was intended to install sizable LED display boards at various spots.
The artificial intelligence-based cameras, which will be installed at each of the city’s train terminals as well, will help track the movement of millions of worshippers, enabling extensive analysis and predictions.
Cameras will also be an essential component of the worshippers’ security. The DRM, Himanshu Badoni, declared during the meeting that advanced technology would be used to guarantee the Mahakumbh’s success.
“We have asked railway officials to give us a list of places where such high-tech cameras can be installed so that they can be used to monitor the movement of devotees as well as to look out for any fraudulent activities,” Garg continued.
The Silicon One series of networking chips, which mark Cisco Systems’ debut into the AI supercomputing market, have just been introduced. With dedicated chips for AI-driven applications, Cisco will now be able to compete directly with market leaders Broadcom and Marvell Technology.
Five of the six major cloud providers are now evaluating Cisco’s networking chips. The company withheld the names of the cloud providers, however, Bofa Global Research reports that major firms including Amazon Web Services, Microsoft Azure, and Google Cloud are involved.
The importance of effective communication between individual chips has been underscored by the expanding demand for AI applications, such as ChatGPT, making Cisco’s networking solutions more and more important.
Cisco, a well-known manufacturer of networking hardware, including ethernet switches, claims that its newest generation of ethernet switches, the G200 and G202, would perform twice as well as its forerunners. Up to 32,000 graphics processing units (GPUs) can be efficiently connected by these switches.
According to Cisco, their chips would allow AI and machine learning activities to be completed with 40% fewer switches, reducing latency and increasing power efficiency.
The news follows Broadcom’s April launch of the Jericho3-AI processor, which similarly bragged about its ability to link up to 32,000 GPU components. This development is a sign of the intensifying industry competitiveness as key competitors compete for control in the market for AI supercomputing, which is expanding quickly.
