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The early innings of the artificial intelligence trade may be over, but Citigroup is staying positive on the tech subsector, viewing cash flows as the key to unlocking the winners of the next phase. "In sum, our message is not to be overly deterred by the significant year-to-date move in profitable AI stocks," the bank said in a Friday note to clients. "Medium- to long-term opportunities still exist as the AI theme has an accelerating growth trajectory and attractive [free cash flow] dynamics that should further improve from here." So far this year, anything connected to AI has seen a significant uptick in valuation, with Nvidia shares leading the pack, surging more than 200%. While the jaw-dropping price action may suggest AI is no longer an early trade, Citi reiterated that the "initial positive thesis" looks intact and warned investors to avoid overlooking free cash flows. Citi expects many names to meet accelerated growth expectations and views free cash flows as "increasingly compelling." "Profitable stocks within this theme are already impressive cash generating machines," the bank wrote. "Recent AI developments should accentuate this characteristic and push FCF margins and growth to new highs." Given this setup, Citi screened for AI-related stocks expected to outpace market growth expectations and experience an uptick in free cash flow margins. Here are some of the stocks that made the cut: Amazon has the highest consensus expectation of more than 48% growth over the long term. Shares have gained almost 54% this year as Wall Street rotates back into technology stocks following the slump in 2022. Some investors have viewed the e-commerce giant as lagging behind its peers in the AI race. During an i nterview with CNBC this month, CEO Andy Jassy soothed some of those concerns, reiterating Amazon's plan to invest in AI across segments. Earlier this year , Amazon also unveiled a generative AI service called Bedrock for its Amazon Web Services unit, allowing clients to use language models to create their own chatbots and image-generation services. Competing chatbot heavyweight Alphabet also made the cut. Shares of the Google parent and Bard creator have rallied 38% as it battles it out with Microsoft -backed OpenAI's ChatGPT. Consensus estimates peg long-term growth at more than 17%, with a near-term free cash flow margin of nearly 24%. GOOGL YTD mountain Alphabet shares in 2023 A handful of financial stocks were also included in Citi's screen. Mastercard offers the greatest near-term free cash flow yield of the group, at 48.4%. Its long-term consensus growth estimate hovers around 19%. Shares have gained about 15% year to date. Ford Motor , Match Group and ServiceNow also made the list. CNBC's Michael Bloom contributed reporting.

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Citi stays positive on A.I. theme and lays out the key to finding ... - CNBC

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Antony Blinken & Gina Raimondo: To shape the future of AI, we must ... - Financial Times

The moment that generative AI applications hit the market, it changed the pace of business not only for security teams, but for cybercriminals too. Today, not embracing AI innovations can mean falling behind your competitors and putting your cyber defense at a disadvantage against cyberattacks powered by AI. But when discussing how AI will or won't impact cybercrime, it's important that we look at things through a pragmatic and sober lens not feeding into hype that reads more like science fiction.

Today's AI advancements and maturity signal a significant leap forward for enterprise security. Cybercriminals can't easily match the size and scale of enterprises' resources, skills, and motivation, making it harder for them to keep up with the current speed of AI innovation. Private venture investment in AI exploded to $93.5 billion in 2021 the bad guys don't have that level of capital. They also don't have the manpower, computing power, and innovations that affords commercial companies or government more time and opportunity to fail quick, learn fast, and get it right first.

Make no mistake, though: Cybercrime will catch up. This is not the first time the security industry has had a brief edge when ransomware started driving more defenders to adopt endpoint detection and response technologies, attackers needed some time to figure out how to circumvent and evade those detections. That interim "grace period" gave businesses time to better shield themselves. The same applies now: Businesses need to maximize on their lead in the AI race, advancing their threat detection and response capabilities and leveraging the speed and precision that current AI innovations afford them.

So how is AI changing cybercrime? Well, it won't change it substantially anytime soon, but it will scale it in certain instances. Let's take at a look at where malicious use of AI will and won't make the most immediate impact.

In recent months, we've seen claims regarding various malicious use cases of AI, but just because a scenario is possible does not make it probable. Take fully automated malware campaigns, for example logic says that it is possible to leverage AI to achieve that outcome, but given that leading tech companies have yet to pioneer fully automated software development cycles, it's unlikely that financially constrained cybercrime groups will achieve this sooner. Even partial automation can enable the scaling of cybercrime, however, a tactic we've already seen used in Bazar campaigns. This is not an innovation, but a tried-and-true technique that defenders are already taking on.

Another use case to consider is AI-engineered phishing attacks. Not only is this one possible, but we're already beginning to see these attacks in the wild. This next generation of phishing may achieve higher levels of persuasiveness and click-rate, but a human-engineered phish and AI-engineered phish still drive toward the same goal. In other words, an AI-engineered phish is still a phish searching for a click, and it requires the same detection and response readiness.

However, while the problem remains the same, the scale is vastly different. AI acts as a force multiplier to scale phishing campaigns, so, if an enterprise is seeing a spike in inbound phishing emails and those malicious emails are significantly more persuasive then it's likely looking at a high click-rate probability and potential for compromise. AI models can also increase targeting efficacy, helping attackers determine who is the most susceptible target for a specific phish within an organization and ultimately reaching a higher ROI from their campaigns. Phishing attacks have historically been among the most successful tactics that attackers have used to infiltrate enterprises. The scaling of this type of attack emphasizes the critical role that EDR, MDR, XDR, and IAM technologies play in detecting anomalous behavior before it achieves impact.

AI poisoning attacks, in other words programmatically manipulating the code and data on which AI models are built, may be the "holy grail" of attacks for cybercriminals. The impact of a successful poisoning attack could range anywhere from misinformation attempts to Die Hard 4.0. Why? Because by poisoning the model, an attacker can make it behave or function in whatever way they want, and it's not easily detectable. However, these attacks aren't easy to carry out they require gaining access to the data the AI model is training on at the time of training, which is no small feat. As more models become open source, the risk of these attacks will increase, but it will remain low for the time being.

While it's important to separate hype from reality, it's also important to ensure we're asking the right questions about AI's impact on the threat landscape. There are lots of unknowns regarding AI's potential how it may change adversaries' goals and objectives is one we mustn't overlook. It remains unknown how new abilities may help serve new purposes for adversaries and recalibrate their motives.

We may not see an immediate spike in novel AI-enabled attacks, but the scaling of cybercrime thanks to AI will have a substantial impact on organizations that aren't prepared. Speed and scale are intrinsic characteristics of AI, and just as defenders are seeking to benefit from them, so are attackers. Security teams are already understaffed and overwhelmed seeing a spike in malicious traffic or incident response engagements is a substantial weight added onto their workload.

This reaffirms more than ever the need for enterprises to invest in their defenses, using AI to drive speed and precision in their threat detection and response capabilities. Enterprises that take advantage of this "grace period" will find themselves much more prepared and resilient for the day attackers actually do catch up in the AI cyber race.

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Are AI-Engineered Threats FUD or Reality? - Dark Reading

Jinjun Xiongs years of experience with artificial intelligence (AI) are making a dramatic impact at UB.

SUNY Empire Innovation Professor of Computer Science and Engineering, Xiong is scientific director and co-director of the AI Institute for Exceptional Education, a national institute developing artificial intelligence systems that identify and assist young children with speech and/or language processing challenges. It was established earlier this year with a five-year, $20 million grant from the National Science Foundation.

Xiong also serves as co-director of UBsInstitute for Artificial Intelligence and Data Science (IAD),where he connects investigators including clinical and translational researchers with the power of AI.

These efforts include:

I am also always looking for new ideas for how we can make the IAD platform more useful and accessible for all UB investigators, Xiong says.

He believes it is important for researchers and the public to understand artificial intelligence, and the ways in which it is changing our world. In a Q&A with UBNow, Xiong discusses the impact of AI on research now and in the future, and analyzes how it will affect health care.

AI is already impacting clinical research in multiple ways, such as medical imagining analyses for skin cancer detection, MRI imaging segmentation, clinical trials data understanding, wearable sensors to improve patient monitoring the list just goes on and on. The future of clinical practices will incorporate more and more intelligent solutions enabled by more efficient and intelligent algorithms, all aiming to improve the patient quality of care. One such example is the growing capabilities of AI, especially the recent amazing results from generative AI like ChatGPT, where it is conceivable that AI-augmented agents such as chatbots can help with providing more accessible and higher-quality health literacy for patients.

To some degree, every future professional needs to understand a bit about AI and computing, by either talking to AI experts/researchers or learning online to gain a general understanding of how AI works, and what AI can do and cannot do right now and even in the near future. With that basic understanding, people working in a particular domain like medicine can revisit their daily practices and think out of the box about where AI can help in their current practice flows, and then engage with an AI expert to co-imagine and then co-design a possible AI-driven solution.

The public should realize that the impact of AI to health care is real and inevitable. There is always an ethical and moral issue around AI in health care, as it may potentially remove autonomy from humans. But that is exactly why the public should be aware of the technology so they can be part of the conversation to find meaningful solutions. I believe the voices of the public should be heard in charting a new direction for humankind with AI.

The power of AI can only become real when it is applied to solve a particular domain problem.

For more information on IAD research initiatives, write to Xiong atjinjun@buffalo.edu.

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QA Qa Xiong - UBNow: News and views for UB faculty and staff - University at Buffalo

Content marketing is crucial for brand awareness and engagement in the digital landscape.

Generating compelling ideas consistently can be daunting, but generative AI like ChatGPT offers solutions.

This article explores top AI tips to boost your content marketing efforts.

AI prompts are any type of text, data, or question that tells the AI the desired response you seek. These prompts can inspire and generate ideas for limitless content marketing concepts.

Before diving into AI-generated prompts, define your content marketing goals. Are you aiming to educate your audience, generate leads or increase brand visibility?

By having clear objectives in mind, you can better tailor your AI prompts to deliver the desired outcomes.

Dig deeper: 8 important content strategy goals to consider

Want to access the full potential of AI prompts? Use platforms that provide advanced language models.

These platforms allow you to generate high-quality prompts by providing relevant instructions and context.

Experiment with different platforms to find the one that aligns with your needs and offers the best results.

Image AI platforms:

Text AI platforms:

AI music platforms:

AI movie generator platforms:

Use AI prompts effectively to pose thought-provoking questions about your industry or niche.

These questions can be excellent starting points for blog posts, social media content or videos.

For example, if you are in the fitness industry, an AI-generated prompt like What are the latest trends in high-intensity interval training? can inspire a comprehensive article that engages your audience.

Prompt ideas:

AI prompts can help you think outside the box and generate unique perspectives on a given topic.

Instead of relying solely on your own expertise, use AI-generated prompts to explore different angles and viewpoints.

This can add depth and diversity to your content, making it more engaging and valuable for your audience.

Prompt ideas:

Dig deeper: Elevate your PPC with ChatGPT: The art of asking disconfirming questions

ChatGPTs responses may not always be perfect or exactly what youre looking for on the first try.

Experiment with different phrasing or approaches to refine your interaction and get closer to your desired unique perspective.

Engage in dialogue

Instead of asking a single question, engage in a back-and-forth conversation with ChatGPT.

Ask follow-up questions and request elaboration to deepen the exploration of ideas. This iterative approach can help generate more nuanced and diverse perspectives.

Incorporate real-world examples

Provide relevant examples or scenarios to ground the conversation in real-life contexts.

This can help ChatGPT draw connections and generate unique perspectives based on its understanding of the world.

Use your creativity

Stuck in a creative rut? AI prompts can act as creative catalysts, sparking new ideas and fresh content concepts.

Experiment with different prompts and instructions to see how AI-generated suggestions can inspire you to think differently.

For instance, a prompt like Write a futuristic scenario envisioning the impact of AI on Medicare Enrollment could lead to an imaginative and thought-provoking piece.

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ChatGPT can comprehend different styles and tones. Here are some styles and examples to help curate your content to get a more specific result.

A formal and authoritative tone suitable for business-related queries or professional discussions.

Example: "Based on extensive research, it can be concluded that..."

Use cases:

A conversational and approachable tone that fosters a casual atmosphere.

Example: "Hey there! I'm here to help you out. What can I assist you with today?"

Use cases:

An objective and informative tone that provides accurate and detailed explanations.

Example: "The process of photosynthesis involves the conversion of sunlight, water, and carbon dioxide into glucose and oxygen."

A lighthearted and fun tone that adds a touch of humor to the conversation.

Example: "Hold on to your hat, because I've got an amazing answer coming your way!"

Use cases

A humorous writing style can make the information more engaging and shareable or even put a fun spin on a conversation with a customer.

A compassionate and understanding tone suitable for discussing sensitive topics or offering emotional support.

Example: "I understand that this situation can be challenging. I'm here to listen and help you through it."

Use cases

Heres a list of prompts that can help you or your team create great ideas:

AI prompts empower content marketers to enhance their creativity and deliver impactful messages that resonate with their audience.

As technology advances, embracing AI in content marketing will become increasingly essential for businesses seeking to stay ahead in the digital landscape.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

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Top AI tips and prompts to supercharge your content marketing - Search Engine Land