The young woman glanced down at his map. "That's over here! What a coincidence, we're going to the same lecture hall. Follow me."
Ethan, quickly recovering from his initial daze, walked beside her. "I appreciate the help. I'm Ethan Blake, just started today."
"I'm Hailey Morgan," she replied, pushing her glasses up her nose with a nervous energy that made her braids bounce. "I'm in Computer Science and AI, too. It's... intense."
"I like intense," Ethan murmured, keeping pace as they crossed the manicured MIT grounds. "So, Hailey, what kind of courses are we starting with? Something practical, I hope?"
"Today is the introductory lecture for Computational Logic and Design," Hailey explained. "It's one of the Core Requirements for the first semester. It sounds complicated, but I think it's about—"
Their conversation was cut short as they entered the large, modern auditorium designated for the introductory lectures. As new freshman students, they were all required to take the same initial classes.
The moment Ethan walked in, he felt the atmosphere shift. His handsome face, impeccably tailored suit, and air of casual wealth made him instantly stand out against the backdrop of serious, sleep-deprived engineering students. The fact that he was walking in casually chatting with Hailey, whom the student body considered one of the few "dignified" female presences in the department, made the glares hostile.
In a faculty dominated by STEM majors, the ratio was notoriously skewed. There were only two women in this particular lecture, and perhaps only six in the entire freshman class for the School of Engineering. The men in the room watched him with the unified suspicion of a threatened pack.
Ethan and Hailey continued talking, oblivious to the simmering resentment, and took two empty seats next to each other in the third row.
Almost immediately, four muscular young men—the kind who hung out at the gym more than the library—marched over. They were known to constantly bother and harass Hailey, considering her, by default of the low numbers, to be their property.
"Well, look who decided to grace us with his presence," sneered the leader, a large man with a crew cut.
A wave of intense, territorial jealousy washed over the group. Ethan recognized the signs of an impending confrontation and felt his boxing instincts instantly activate, ready to neutralize the threat.
"Get out of my seat, preppy," the leader spat, pushing his chest out at Ethan. The boy misinterpreted Ethan's initial silence as cowardice, assuming this flashy newcomer would fold easily.
Before Ethan could move or respond, the door at the front of the auditorium opened sharply. A very serious, extremely square-looking professor—the kind whose posture suggested he was molded from pure concrete—walked to the podium.
The entire auditorium instantly fell silent. Every student scrambled to their seats.
"Everyone sit down. Now," the professor stated flatly.
The aggressive student had no choice. He stood over Ethan, his fists clenched, before leaning in and whispering through gritted teeth: "You're dead, you asshole."
Ethan simply ignored him, his expression one of perfect indifference. The student was forced to stomp away, seething, and find another spot just as the professor began the lecture.
The professor, whose nametag identified him as Dr. Aris Thorne, did not waste a second. "Welcome to 6.042J, Computational Logic and Design. You may address me as Dr. Thorne. Today, we begin with a problem designed to assess your current mental aptitude. Take out your notebooks."
Dr. Thorne walked over to the whiteboard and wrote down a complex problem involving Modular Arithmetic and cryptographic hashing—a topic usually reserved for the middle of the semester.
"This is an elementary problem in discrete mathematics, often used to optimize hash table access," Dr. Thorne droned. "For a given hash function h(k) equals k module m where m equals 17 and we have keys k equal to the set {15, 32, 49, 66, 83}, demonstrate a pattern that minimizes collisions while remaining computationally efficient."
The auditorium filled with the collective sound of pencils scratching and frantic page-flipping.
Hailey, sitting next to Ethan, quickly pulled out her own textbook, her brow furrowed in confusion. "W-wait, this is a mid-semester topic. We haven't covered the Chinese Remainder Theorem yet," she whispered to Ethan, clearly stressed.
Ethan barely glanced at the board. He remembered studying this exact concept in detail during his prep for Harvard, and his time working at FixLT HUB had given him extensive practical experience programming routing algorithms and machine logic.
He raised his hand calmly.
Dr. Thorne looked up, annoyed by the interruption. "Yes, the young man in the suit? Do you have an issue with the complexity of the problem?"
"No, sir," Ethan replied, his voice ringing clearly across the quiet room. "The solution is to restructure m to be a prime number near the powers of 2, specifically m equals 17, as you already have. Since the key set k follows a simple arithmetic progression where each key is 15 plus 17 times a number, the hash function h(k) will always return 15 for every key.
"The hash function is correct, but the chosen keys are the problem. You will achieve 100 percent collisions, regardless of the method, because every key in that specific set is mathematically equivalent to 15 when divided by 17. It's an effective demonstration of a bad key set."
A wave of murmuring swept through the lecture hall. Dr. Thorne's severe expression didn't change, but a flicker of grudging respect crossed his eyes.
"Correct, Mr....?"
"Blake, Ethan Blake."
"Mr. Blake. You recognized the pattern quickly. Good. The pattern was intended to illustrate the limitations of simple division hashing," Dr. Thorne conceded, then quickly moved on.
Hailey stared at Ethan, her mouth slightly agape. "How did... how did you know that? It's so fast!"
Ethan shrugged, already pulling out his phone. "It's just logic, Hailey. Elementary stuff."
He quickly activated his privacy firewall and found Lena Rossi's number. He had $70 million that needed to stop looking like drug money and start looking like seed capital.
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